Artículos de revistas sobre el tema "[INFO:INFO_OH] Computer Science/Other"

Researchers are interested in defining decision support systems that can act in contexts characterized by uncertainty and info-incompleteness. The present study proposes a learning model for assessing the relevance of probability, plausibility, credibility, and possibility opinions in the conditions above. The solution consists of an Artificial Neural Network acquiring input features related to the considered set of opinions and other relevant attributes. The model provides the weights for minimizing the error between the expected outcome and the ground truth concerning a given phenomenon of interest. A custom loss function was defined to minimize the Mean Best Price Error (MBPE), while the evaluation of football players’ was chosen as a case study for testing the model. A custom dataset was constructed by scraping the Transfermarkt, Football Manager, and FIFA21 information sources and by computing a sentiment score through BERT, obtaining a total of 398 occurrences, of which 85% were employed for training the proposed model. The results show that the probability opinion represents the best choice in conditions of info-completeness, predicting the best price with 0.86 MBPE (0.61% of normalized error), while an arbitrary set composed of plausibility, credibility, and possibility opinions was considered for deciding successfully in info-incompleteness, achieving a confidence score of 2.47±0.188 MBPE (1.89±0.15% of normalized error). The proposed solution provided high performance in predicting the transfer cost of a football player in conditions of both info-completeness and info-incompleteness, revealing the significance of extending the feature space to opinions concerning the quantity to predict. Furthermore, the assumptions of the theoretical background were confirmed, as well as the observations found in the state of the art regarding football player evaluation.

In the scorching and sultry heat of a Mumbai summer Prem Yadav, the Director of Pratham Info Tech Foundation (referred to as the Foundation), Mumbai, India and his team were busy teaching basic computer skills to students attending a school for children raised in poor households. These children were stumbling at every stage. Classrooms were very small and congested. Electricity supply was erratic. Software products were available only in English and were not compatible with the hardware. Schools and teachers were unenthusiastic if not wary of the additional burden put on them. This was the situation in spite of the fact that for four years since 1998, Prem and his team had tried everything to integrate Information and Communication Technology (ICT) in 54 Municipal Corporation schools, (schools run by the civic body that governs the city) started mainly for unprivileged children. The team enjoyed moderate success, but the overall impact was small. Uses of ICT in education were perceived to be an add-on support, rather than an effective toolbox to bring consistency and equality in providing quality education and empowerment to underprivileged children. Information technology had led to decisive and sweeping changes in other fields like healthcare, e-governance, logistics, and manufacturing. Yet so far ICT had very limited success in the field of education especially at pre-primary and secondary school levels (i.e., from standard 1st to 8th). On the one hand, India was emerging as a knowledge based economy by exporting IT and IT based services to the world, and, on the other hand, most of the population belonging to the low income group did not have any access to learn basic knowledge and skills related to IT. Prem was convinced that this digital gap needed to be closed as early as possible; otherwise India would risk leaving a large section of the population far behind. He knew that it was not the technology per se, but the implementation of the technology at the grass roots level that was more important.

Personalized suggestions are important to help users find relevant information. It often depends on huge collection of user data, especially users’ online activity (e.g., liking/commenting/sharing) on social media, thereto user interests. Publishing such user activity makes inference attacks easy on the users, as private data (e.g., contact details) are often easily gathered from the users’ activity data. during this module, we proposed PrivacyRank, an adjustable and always protecting privacy on social media data publishing framework , which protects users against frequent attacks while giving personal ranking based recommendations. Its main idea is to continuously blur user activity data like user-specified private data is minimized under a given data budget, which matches round the ranking loss suffer from the knowledge blurring process so on preserve the usage of the info for enabling suggestions. a true world evaluation on both synthetic and real-world datasets displays that our model can provide effective and continuous protection against to the info given by the user, while still conserving the usage of the blurred data for private ranking based suggestion. Compared to other approaches, Privacy Rank achieves both better privacy protection and a far better usage altogether the rank based suggestions use cases we tested.

Purpose The purpose of this study is to investigate how smart tourism technologies and memorable tourism experiences affect tourist satisfaction and tourist destination loyalty. Design/methodology/approach A total of 600 questionnaires were distributed, 360 were returned (60% response rate) and a covariance-based structural equation modeling technique was used to test the hypotheses. Findings The results of this study explain that smart tourism technologies and memorable tourism experiences play essential roles in enhancing tourist satisfaction and tourist destination loyalty. Practical implications This study specifies that tourists have pleasant memories and are satisfied at a tourist destination; as a result, they are more likely to revisit and recommend a tourist destination to their friends, family and other tourists. If a tourist has a negative experience with smart city info-structure facilities, a tourist might reach an overall conclusion to not revisit or recommend the location to other tourists. Originality/value This study provides empirical evidence to support the importance of smart tourism technologies and memorable tourism experiences in enhancing tourist satisfaction and tourist destination loyalty.

Abstract: One of the applications of technology in the world of education is the digital dissemination of information on social media or other online media by education providers about their school profiles so that they are more widely known to the public. STMIK Royal through the Media and Information institution is currently using social media platforms such as Instagram, Facebook, Twitter, Youtube, and Tiktok in disseminating information about its campus, both regarding new student admissions, info on academic activities, as well as information about announcements or policies that made. The application is built on a desktop basis with a client-server concept so that all work data originating from the creative team's computers in the STMIK Royal Media and Information office can be centralized on one computer. With a basic field of knowledge, research research groups, and focus on teaching courses from researchers, namely the field of Computer Science with the Software Engineering research group and teaching Visual Programming courses, this research will be carried out very maturely and seriously to produce application products according to what is expected. needed and usable..Keywords: desktop applications, client servers, media and information Abstrak: Salah satu penerapan teknologi dalam dunia pendidikan adalah penyebaran informasi secara digital di media sosial ataupun media online lainnya oleh penyelenggara pendidikan tentang profil sekolahnya agar lebih banyak dikenal masyarakat. STMIK Royal melalui lembaga Media dan Informasi saat ini sudah menggunakan platform media sosial seperti Instagram, Facebook, Twitter, Youtube, dan Tiktok dalam penyebaran informasi-informasi seputar kampusnya, baik tentang penerimaan mahasiswa baru, info kegiatan akademik, juga informasi mengenaik pengumuman atau kebijakan yang dibuat. Aplikasi yang dibangun berbasis desktop dengan konsep client-server agar seluruh data pekerjaan yang berasal dari komputer-komputer tim kreatif yang ada di kantor Media dan Informasi STMIK Royal bisa terpusat pada satu komputer. Dengan dasar bidang ilmu, kelompok bidang riset penelitian, dan fokus pengajaran mata kuliah dari peneliti yaitu bidang Ilmu Komputer dengan kelompok riset penelitian Software Engineering dan mengajar mata kuliah Pemrograman Visual, menjadikan penelitian ini akan dikerjakan dengan sangat matang dan serius hingga menghasilkan produk aplikasi sesuai yang dibutuhkan dan bisa dipakai. ? Kata kunci: aplikasi desktop, client server, media dan informasi

The main sources of greenhouse gas emissions and air pollution from the transport sector are diesel- and gasoline-powered passenger cars. The combustion of large amounts of conventional fuels by cars contributes to a significant release of various compounds into the atmosphere, such as solid particles, nitrogen oxides, carbon monoxide, and carbon dioxide. In order to reduce these pollutants in places of their high concentration (especially in urban agglomerations), the use of ecological means of transport for daily driving is highly recommended. Electric vehicles (EV) are characterized by ecological potential due to their lack of direct emissions and low noise. However, in Poland and many other countries, electricity production is still based on fossil fuels which can significantly influence the indirect emissions of carbon dioxide into the atmosphere associated with battery charging. Thus, indirect emissions from electric cars may be comparable or even higher than direct emissions related to the use of traditional cars. Therefore, the aim of the work was to analyze the amount of carbon dioxide emissions associated with the use of electric vehicles for daily driving (City, Sedan, SUV) and their impact on the environment on a local and global scale. Based on the assumed daily number of kilometers driven by the vehicle and the collected certified catalog data (Car Info Nordic AB), the direct emissions generated by the internal combustion engines (ICE) were calculated for specific cars. These values were compared to the indirect emissions related to the source of electricity generation, for the calculation of which the CO2 emission coefficient for a particular energy source and energy mix was used, as well as reference values of electricity generation efficiency in a given combustion installation, in accordance with the KOBiZE (The National Centre for Emissions Management) and European Union regulation. Indirect emissions generated from non-renewable fuels (lignite, hard coal, natural gas, diesel oil, heating oil, municipal waste) and renewable emissions (wind energy, solar energy, hydro energy, biomass, biogas) were considered. The results indicated that for the Polish case study, indirect carbon dioxide emission associated with the daily driving of EV (distance of 26 km) ranges 2.49–3.28 kgCO2∙day−1. As a result, this indirect emission can be even higher than direct emissions associated with ICE usage (2.55–5.64 kgCO2∙day−1).

Since the inception of the current COVID-19 pandemic, related misleading information has spread at a remarkable rate on social media, leading to serious implications for individuals and societies. Although COVID-19 looks to be ending for most places after the sharp shock of Omicron, severe new variants can emerge and cause new waves, especially if the variants can evade the insufficient immunity provided by prior infection and incomplete vaccination. Fighting the fake news that promotes vaccine hesitancy, for instance, is crucial for the success of the global vaccination programs and thus achieving herd immunity. To combat the proliferation of COVID-19-related misinformation, considerable research efforts have been and are still being dedicated to building and sharing COVID-19 misinformation detection datasets and models for Arabic and other languages. However, most of these datasets provide binary (true/false) misinformation classifications. Besides, the few studies that support multi-class misinformation classification deal with a small set of misinformation classes or mix them with situational information classes. False news stories about COVID-19 are not equal; some tend to have more sinister effects than others (e.g., fake cures and false vaccine info). This suggests that identifying the sub-type of misinformation is critical for choosing the suitable action based on their level of seriousness, ranging from assigning warning labels to the susceptible post to removing the misleading post instantly. We develop comprehensive annotation guidelines in this work that define 19 fine-grained misinformation classes. Then, we release the first Arabic COVID-19-related misinformation dataset comprising about 6.7K tweets with multi-class and multi-label misinformation annotations. In addition, we release a version of the dataset to be the first Twitter Arabic dataset annotated exclusively with six different situational information classes. Identifying situational information (e.g., caution, help-seeking) helps authorities or individuals understand the situation during emergencies. To confirm the validity of the collected data, we define three classification tasks and experiment with various machine learning and transformer-based classifiers to offer baseline results for future research. The experimental results indicate the quality and validity of the data and its suitability for constructing misinformation and situational information classification models. The results also demonstrate the superiority of AraBERT-COV19, a transformer-based model pretrained on COVID-19-related tweets, with micro-averaged F-scores of 81.6% and 78.8% for the multi-class misinformation and situational information classification tasks, respectively. Label Powerset with linear SVC achieved the best performance among the presented methods for multi-label misinformation classification with micro-averaged F-scores of 76.69%.

Objective Researchers have used various theories and models to understand technology adoption, however, with the growing interest and availability of mobile applications (apps) for people living with dementia, it is desirable to have a broader insight into how technology adoption may be further improved. This paper aims to explore the factors influencing the adoption of digital health applications for people living with dementia and add to the current literature on this topic. Methods Searches were conducted in CINHAL, Web of Science, Psych Info, ProQuest Health and Medical, IEEE Xplore and Scopus. Citation searching and handsearching were used in the identification of other studies. Results Following an assessment of relevancy, nine studies remained and are included within this review. Methodological quality was assessed using The Mixed Methods Appraisal Tool (MMAT). A thematic analysis was used for the data synthesis of included studies. Each study reported on different types of apps. Conclusion From the synthesis of included studies, four analytic themes were identified; Theme 1: Personal and contextual factors; Theme 2: Perceived value and benefit; Theme 3: Design and content of app; and Theme 4: Digital Literacy and Confidence. People are diverse and so are their reasons for the adoption of apps. These findings provide an insight into the range of factors that impact the adoption of apps for people living with dementia. Understanding the factors that impact the adoption of mobile applications is critical to their success. These findings can be beneficial for app developers and for people living with dementia and their carers.

Extended Clifford circuits straddle the boundary between classical and quantum computational power. Whether such circuits are efficiently classically simulable seems to depend delicately on the ingredients of the circuits. While some combinations of ingredients lead to efficiently classically simulable circuits, other combinations, which might just be slightly different, lead to circuits which are likely not. We extend the results of Jozsa and Van den Nest [Quant. Info. Comput. 14, 633 (2014)] by studying two further extensions of Clifford circuits. First, we consider how the classical simulation complexity changes when we allow for more general measurements. Second, we investigate different notions of what it means to ‘classically simulate’ a quantum circuit. These further extensions give us 24 new combinations of ingredients compared to Jozsa and Van den Nest, and we give a complete classification of their classical simulation complexities. Our results provide more examples where seemingly modest changes to the ingredients of Clifford circuits lead to “large” changes in the classical simulation complexities of the circuits, and also include new examples of extended Clifford circuits that exhibit “quantum supremacy”, in the sense that it is not possible to efficiently classically sample from the output distributions of such circuits, unless the polynomial hierarchy collapses.

The fine particulate matter (PM2.5) concentration has been a vital source of info and an essential indicator for measuring and studying the concentration of other air pollutants. It is crucial to realize more accurate predictions of PM2.5 and establish a high-accuracy PM2.5 prediction model due to their social impacts and cross-field applications in geospatial engineering. To further boost the accuracy of PM2.5 prediction results, this paper proposes a new wavelet PM2.5 prediction system (called WD-OSMSSA-KELM model) based on a new, improved variant of the salp swarm algorithm (OSMSSA), kernel extreme learning machine (KELM), wavelet decomposition, and Boruta-XGBoost (B-XGB) feature selection. First, we applied the B-XGB feature selection to realize the best features for predicting hourly PM2.5 concentrations. Then, we applied the wavelet decomposition (WD) algorithm to reach the multi-scale decomposition results and single-branch reconstruction of PM2.5 concentrations to mitigate the prediction error produced by time series data. In the next stage, we optimized the parameters of the KELM model under each reconstructed component. An improved version of the SSA is proposed to reach higher performance for the basic SSA optimizer and avoid local stagnation problems. In this work, we propose new operators based on oppositional-based learning and simplex-based search to mitigate the core problems of the conventional SSA. In addition, we utilized a time-varying parameter instead of the main parameter of the SSA. To further boost the exploration trends of SSA, we propose using the random leaders to guide the swarm towards new regions of the feature space based on a conditional structure. After optimizing the model, the optimized model was utilized to predict the PM2.5 concentrations, and different error metrics were applied to evaluate the model’s performance and accuracy. The proposed model was evaluated based on an hourly database, six air pollutants, and six meteorological features collected from the Beijing Municipal Environmental Monitoring Center. The experimental results show that the proposed WD-OLMSSA-KELM model can predict the PM2.5 concentration with superior performance (R: 0.995, RMSE: 11.906, MdAE: 2.424, MAPE: 9.768, KGE: 0.963, R2: 0.990) compared to the WD-CatBoost, WD-LightGBM, WD-Xgboost, and WD-Ridge methods.

Spot panchromatic satellite image had been employed to study and know the difference Between ground and satellite data( DN ,its values varies from 0-255) where it is necessary to convert these DN values to absolute radiance values through special equations ,later it converted to spectral reflectance values .In this study a monitoring of the environmental effect resulted from throwing the sewage drainages pollutants (industrial and home) into the Tigris river water in Mosul, was achieved, which have an effect mostly on physical characters specially color and turbidity which lead to the variation in Spectral Reflectance of the river water ,and it could be detected by using many remote sensing techniques. The contaminated areas within the water of the river which represents the difference in the reflectance values were isolated and signed, as well as the field estimations, which had been done by using spectrometer device, which gave an acceptable agreement with satellite data considering time difference between these estimations. satellite imagery analysis program ERDAS version 8.4 was used to determine the values of Spectral Reflectance in the satellite image. A geographic information systems through the ARC INFO has been used to draw photo map of the study area determined it specific sites of measuring the Reflectance, which represent areas that are near the sources of pollution and the other various regions along the river.

Deceptive content recognition in social media employing artificial intelligence (AI) includes the use of sophisticated techniques and machine learning (ML) methods to recognize deceptive or wrong data shared on numerous platforms. AI methods analyse textual as well as multimedia content, investigative patterns, linguistic cues, and contextual info to flag latent cases of deception. As a result of the use of natural language processing (NLP) and computer vision (CV), these systems identify subtle nuances, misrepresentation strategies, and anomalies in user-generated content. This active technique permits social media platforms, organizations, and consumers to recognize and diminish the spread of deceptive content, donates to a more reliable online atmosphere, and aids in fighting tasks modelled by misinformation and false news. This study offers a novel sine cosine algorithm with deep learning-based deceptive content detection on social media (SCADL-DCDSM) technique. The SCADL-DCDSM technique incorporates the ensemble learning process with a hyperparameter tuning strategy for classifying the sentiments. Primarily, the SCADL-DCDSM technique pre-processes the input data to change the input data into a valuable format. Moreover, the SCADL-DCDSM algorithm follows the BERT model for the word embedding process. Moreover, the SCADL-DCDSM technique involves an ensemble of three models for sentiment classification such as long short-term memory (LSTM), extreme learning machine (ELM), and attention-based recurrent neural network (ARNN). Finally, SCA can be executed for better hyperparameter choice of the DL models. The SCADL-DCDSM system integrates the explainable artificial intelligence (XAI) system LIME has been employed for a comprehensive explainability and understanding of the black-box process, enhancing correct deceptive content recognition. The simulation result analysis of the SCADL-DCDSM algorithm has been examined on a benchmark database. The simulation outcome illustrated that the SCADL-DCDSM methodology achieves optimum solution than other approaches in terms of different measures.

The main goal of the work is to create the optimal emergency evacuation plan in general education institutions according to the schedule at a certain time. The work developed an information model of the evacuation system, taking into account the schedule of classes and classrooms. The methodology of the system approach, which ensures the compatibility of heterogeneous devices to find an operationally optimal evacuation plan in real time, was developed. A conceptual scheme of an evacuation system using heterogeneous sources of receiving and transmitting information about emergencies is proposed. Determined the input and output sources of receiving and transmitting information about the number of people in the building. Developed software for the rapid and most effective evacuation of people from the educational institution and can be used for other types of buildings. The importance of this work is the creation of an integrated evacuation information system based on mathematical modeling of multi-criteria optimization problem of flow distribution and design, construction technology receiving and transmitting data and information notification systems for the selected type of building. in order to adopt an operational evacuation plan. The results of this paper allow the systematic organization of evacuation training, preparing resources so that in the event of an emergency it is possible to quickly respond and conduct the evacuation process to avoid major consequences. The use of information technology greatly increases the efficiency of evacuation systems, so the development of new integrated and intelligent info-communication approaches to solve the problem of evacuation is currently very relevant

AbstractIn order to assure accurate modelling, this study presents a new technique for appropriately modelling and simulating a proton exchange membrane fuel cell (PEMFC) system. The PEMFC is a cleaner and more sustainable energy source as compared to fossil fuels. The fundamental idea is to minimize the sum of squared error (SSE) between the estimated and measured output voltage for the Ballard Mark V model in order to identify the model parameters of PEMFC stacks as efficiently as possible using a newly developed meta-heuristic called enhanced efficient optimization algorithm (EINFO). The proposed optimizer is considered an enhanced version of the original INFO algorithm. By balancing the exploration and exploitation phases better, the EINFO algorithm is intended to improve the performance of the original INFO approach and prevent local optima. The new method was tested on 23 benchmark functions and compared to the original INFO algorithm as well as other recently evolved optimizers. The algorithm is examined and compared with some literature meta-heuristics, including the particle swarm optimization, sine cosine algorithm, dragonfly algorithm, atom search optimization, Harris hawks optimization, and efficient optimization algorithm, using 50 independent runs, in terms of convergence speed and least SSE. When compared to other methods, the final findings show that, the suggested technique achieves the fastest convergence speed.

‘We are faced today with an entire system of communication technology which is the perfect medium to host and transfer the very programs designed to destroy the functionality of the system.’ (IBM Researcher: Sarah Gordon, 1995) Despite renewed interest in open source code, the openness of the information space is nothing new in terms of the free flow of information. The transitive and nonlinear configuration of data flow has ceaselessly facilitated the sharing of code. The openness of the info-space encourages a free distribution model, which has become central to numerous developments through the abundant supply of freeware, shareware and source code. Key moments in open source history include the release in 1998 of Netscape’s Communicator source code, a clear attempt to stimulate browser development. More recently in February 2004 the ‘partial leaking’ of Microsoft Windows 2000 and NT 4.0 source code demonstrated the often-hostile disposition of open culture and the potential threat it poses to existing corporate business models. However, the leading exponents of the open source ethic predate these events by more than a decade. As an extension of the hacker, the virus writer has managed, since the 1980s, to bend the shape of info-space beyond recognition. By freely spreading viruses, worms and hacker programs across the globe, virus writers have provided researchers with a remarkable set of digital footprints to follow. The virus has, as IBM researcher Sarah Gordon points out, exposed the info-space as a ‘perfect medium’ rife for malicious viral infection. This paper argues that viral technologies can hold info-space hostage to the uncertain undercurrents of information itself. As such, despite mercantile efforts to capture the spirit of openness, the info-space finds itself frequently in a state far-from-equilibrium. It is open to often-unmanageable viral fluctuations, which produce levels of spontaneity, uncertainty and emergent order. So while corporations look to capture the perpetual, flexible and friction-free income streams from centralised information flows, viral code acts as an anarchic, acentred Deleuzian rhizome. It thrives on the openness of info-space, producing a paradoxical counterpoint to a corporatised information society and its attempt to steer the info-machine. The Virus in the Open System Fred Cohen’s 1984 doctoral thesis on the computer virus locates three key features of openness that makes viral propagation possible (see Louw and Duffy, 1992 pp. 13-14) and predicts a condition common to everyday user experience of info-space. Firstly, the virus flourishes because of the computer’s capacity for information sharing_; transitive flows of code between nodes via discs, connected media, network links, user input and software use. In the process of information transfer the ‘witting and unwitting’ cooperation of users and computers is a necessary determinant of viral infection. Secondly, information flow must be _interpreted._ Before execution computers interpret incoming information as a series of instructions (strings of bits). However, before execution, there is no fundamental distinction between information received, and as such, information has no _meaning until it has been executed. Thus, the interpretation of information does not differentiate between a program and a virus. Thirdly, the alterability or manipulability of the information process allows the virus to modify information. For example, advanced polymorphic viruses avoid detection by using non-significant, or redundant code, to randomly encrypt and decrypt themselves. Cohen concludes that the only defence available to combat viral spread is the ‘limited transitivity of information flow’. However, a reduction in flow is contrary to the needs of the system and leads ultimately to the unacceptable limitation of sharing (Cohen, 1991). As Cohen states ‘To be perfectly secure against viral attacks, a system must protect against incoming information flow, while to be secure against leakage of information a system must protect against outgoing information flow. In order for systems to allow sharing, there must be some information flow. It is therefore the major conclusion of this paper that the goals of sharing in a general purpose multilevel security system may be in such direct opposition to the goals of viral security as to make their reconciliation and coexistence impossible.’ Cohen’s research does not simply end with the eradication of the virus via the limitation of openness, but instead leads to a contentious idea concerning the benevolent properties of viral computing and the potential legitimacy of ‘friendly contagion’. Cohen looks beyond the malevolent enemy of the open network to a benevolent solution. The viral ecosystem is an alternative to Turing-von Neumann capability. Key to this system is a benevolent virus,_ which epitomise the ethic of open culture. Drawing upon a biological analogy, benevolent viral computing _reproduces in order to accomplish its goals; the computing environment evolving_ rather than being ‘designed every step of the way’ (see Zetter, 2000). The _viral ecosystem_ demonstrates how the spread of viruses can purposely _evolve through the computational space using the shared processing power of all host machines. Information enters the host machine via infection and a translator program alerts the user. The benevolent virus_ passes through the host machine with any additional modifications made by the _infected_ _user. The End of Empirical Virus Research? Cohen claims that his research into ‘friendly contagion’ has been thwarted by network administrators and policy makers (See Levy, 1992 in Spiller, 2002) whose ‘apparent fear reaction’ to early experiments resulted in trying to solve technical problems with policy solutions. However, following a significant increase in malicious viral attacks, with estimated costs to the IT industry of $13 billion in 2001 (Pipkin, 2003 p. 41), research into legitimate viruses has not surprisingly shifted from the centre to the fringes of the computer science community (see Dibbell, 1995)._ _Current reputable and subsequently funded research tends to focus on efforts by the anti-virus community to develop computer hygiene. Nevertheless, malevolent or benevolent viral technology provides researchers with a valuable recourse. The virus draws analysis towards specific questions concerning the nature of information and the culture of openness. What follows is a delineation of a range of approaches, which endeavour to provide some answers. Virus as a Cultural Metaphor Sean Cubitt (in Dovey, 1996 pp. 31-58) positions the virus as a contradictory cultural element, lodged between the effective management of info-space and the potential for spontaneous transformation. However, distinct from Cohen’s aspectual analogy, Cubitt’s often-frivolous viral metaphor overflows with political meaning. He replaces the concept of information with a space of representation, which elevates the virus from empirical experience to a linguistic construct of reality. The invasive and contagious properties of the biological parasite are metaphorically transferred to viral technology; the computer virus is thus imbued with an alien otherness. Cubitt’s cultural discourse typically reflects humanist fears of being subjected to increasing levels of technological autonomy. The openness of info-space is determined by a managed society aiming to ‘provide the grounds for mutation’ (p. 46) necessary for profitable production. Yet the virus, as a possible consequence of that desire, becomes a potential opposition to ‘ideological formations’. Like Cohen, Cubitt concludes that the virus will always exist if the paths of sharing remain open to information flow. ‘Somehow’, Cubitt argues, ‘the net must be managed in such a way as to be both open and closed. Therefore, openness is obligatory and although, from the point of view of the administrator, it is a recipe for ‘anarchy, for chaos, for breakdown, for abjection’, the ‘closure’ of the network, despite eradicating the virus, ‘means that no benefits can accrue’ (p.55). Virus as a Bodily Extension From a virus writing perspective it is, arguably, the potential for free movement in the openness of info-space that that motivates the spread of viruses. As one writer infamously stated it is ‘the idea of making a program that would travel on its own, and go to places its creator could never go’ that inspires the spreading of viruses (see Gordon, 1993). In a defiant stand against the physical limitations of bodily movement from Eastern Europe to the US, the Bulgarian virus writer, the Dark Avenger, contended that ‘the American government can stop me from going to the US, but they can’t stop my virus’. This McLuhanesque conception of the virus, as a bodily extension (see McLuhan, 1964), is picked up on by Baudrillard in Cool Memories_ _(1990). He considers the computer virus as an ‘ultra-modern form of communication which does not distinguish, according to McLuhan, between the information itself and its carrier.’ To Baudrillard the prosperous proliferation of the virus is the result of its ability to be both the medium and the message. As such the virus is a pure form of information. The Virus as Information Like Cohen, Claude Shannon looks to the biological analogy, but argues that we have the potential to learn more about information transmission in artificial and natural systems by looking at difference rather than resemblance (see Campbell, 1982). One of the key aspects of this approach is the concept of redundancy. The theory of information argues that the patterns produced by the transmission of information are likely to travel in an entropic mode, from the unmixed to the mixed – from information to noise. Shannon’s concept of redundancy ensures that noise is diminished in a system of communication. Redundancy encodes information so that the receiver can successfully decode the message, holding back the entropic tide. Shannon considers the transmission of messages in the brain as highly redundant since it manages to obtain ‘overall reliability using unreliable components’ (in Campbell, 1982 p. 191). While computing uses redundancy to encode messages, compared to transmissions of biological information, it is fairly primitive. Unlike the brain, Turing-von-Neumann computation is inflexible and literal minded. In the brain information transmission relies not only on deterministic external input, but also self-directed spontaneity and uncertain electro-chemical pulses. Nevertheless, while Shannon’s binary code is constrained to a finite set of syntactic rules, it can produce an infinite number of possibilities. Indeed, the virus makes good use of redundancy to ensure its successful propagation. The polymorphic virus is not simply a chaotic, delinquent noise, but a decidedly redundant form of communication, which uses non-significant code to randomly flip itself over to avoid detection. Viral code thrives on the infinite potential of algorithmic computing; the open, flexible and undecidable grammar of the algorithm allows the virus to spread, infect and evolve. The polymorphic virus can encrypt and decrypt itself so as to avoid anti-viral scanners checking for known viral signatures from the phylum of code known to anti-virus researchers. As such, it is a raw form of Artificial Intelligence, relying on redundant inflexible_ _code programmed to act randomly, ignore or even forget information. Towards a Concept of Rhizomatic Viral Computation Using the concept of the rhizome Deleuze and Guattari (1987 p. 79) challenge the relation between noise and pattern established in information theory. They suggest that redundancy is not merely a ‘limitative condition’, but is key to the transmission of the message itself. Measuring up the efficiency of a highly redundant viral transmission against the ‘splendour’ of the short-term memory of a rhizomatic message, it is possible to draw some conclusions from their intervention. On the surface, the entropic tendency appears to be towards the mixed and the running down of the system’s energy. However, entropy is not the answer since information is not energy; it cannot be conserved, it can be created and destroyed. By definition information is something new, something that adds to existing information (see Campbell, 1982 p. 231), yet efficient information transmission creates invariance in a variant environment. In this sense, the pseudo-randomness of viral code, which pre-programs elements of uncertainty and free action into its propagation, challenges the efforts to make information centralised, structured and ordered. It does this by placing redundant noise within its message pattern. The virus readily ruptures the patterned symmetry of info-space and in terms of information produces something new. Viral transmission is pure information as its objective is to replicate itself throughout info-space; it mutates the space as well as itself. In a rhizomatic mode the anarchic virus is without a central agency; it is a profound rejection of all Generals and power centres. Viral infection, like the rhizomatic network, is made up of ‘finite networks of automata in which communication runs from any neighbour to any other’. Viral spread flows along non-pre-existent ‘channels of communication’ (1987 p. 17). Furthermore, while efforts are made to striate the virus using anti-viral techniques, there is growing evidence that viral information not only wants to be free, but is free to do as it likes. About the Author Tony Sampson is a Senior Lecturer and Course Tutor in Multimedia & Digital Culture, School of Cultural and Innovation Studies at the University of East London, UK Email: t.d.sampson@uel.ac.uk Citation reference for this article MLA Style Sampson, Tony. "A Virus in Info-Space" M/C: A Journal of Media and Culture <http://www.media-culture.org.au/0406/07_Sampson.php>. APA Style Sampson, T. (2004, Jul1). A Virus in Info-Space. M/C: A Journal of Media and Culture, 7, <http://www.media-culture.org.au/0406/07_Sampson.php>

The University of New Mexico (UNM) embarked on a project funded by the National Science Foundation (NSF) to engage in activities that are believed to support retention and graduation of STEM students (specifically engineering and computer science students). The project focused on the following activities: internships, faculty-mentoring and other career development activities such as conferences, interacting with industry, financial aid info, resume building workshops, interview skills workshops. The project focused on early career students (mostly sophomores and some freshmen). The methods of this research involved data collection and analysis, surveys, bivariate descriptive statistics with statistical significance, and multivariate logistic regression analysis. The authors have found evidence supporting that such activities have played a positive role in student’s continued retention, eventual graduation and overall self-confidence in their engineering/computing persona going forward. Other higher education institutions are encouraged to pursue similar activities.

Abstract Background ImputAccur is a software tool to measure genotype-imputation accuracy. Imputation of untyped markers is a standard approach in genome-wide association studies to close the gap between directly genotyped and other known DNA variants. However, high accuracy for imputed genotypes is fundamental. Several accuracy measures have been proposed, but unfortunately, they are implemented on different platforms, which is impractical. Results With ImputAccur, the accuracy measures info, Iam-hiQ and r2-based indices can be derived from standard output files of imputation software. Sample/probe and marker filtering is possible. This allows e.g. accurate marker filtering ahead of data analysis. Conclusions The source code (Python version 3.9.4), a standalone executive file, and example data for ImputAccur are freely available at https://gitlab.gwdg.de/kolja.thormann1/imputationquality.git.

Abstract Background Imputation of untyped markers is a standard tool in genome-wide association studies to close the gap between directly genotyped and other known DNA variants. However, high accuracy with which genotypes are imputed is fundamental. Several accuracy measures have been proposed and some are implemented in imputation software, unfortunately diversely across platforms. In the present paper, we introduce Iam hiQ, an independent pair of accuracy measures that can be applied to dosage files, the output of all imputation software. Iam (imputation accuracy measure) quantifies the average amount of individual-specific versus population-specific genotype information in a linear manner. hiQ (heterogeneity in quantities of dosages) addresses the inter-individual heterogeneity between dosages of a marker across the sample at hand. Results Applying both measures to a large case–control sample of the International Lung Cancer Consortium (ILCCO), comprising 27,065 individuals, we found meaningful thresholds for Iam and hiQ suitable to classify markers of poor accuracy. We demonstrate how Manhattan-like plots and moving averages of Iam and hiQ can be useful to identify regions enriched with less accurate imputed markers, whereas these regions would by missed when applying the accuracy measure info (implemented in IMPUTE2). Conclusion We recommend using Iam hiQ additional to other accuracy scores for variant filtering before stepping into the analysis of imputed GWAS data.

AbstractFrom the point of production to consumption, electrical energy should be utilized effectively and qualitatively. Efficiency at the electricity consumption stage is not sufficient, and the desired criteria must be met at the production stage. The efficient and high‐quality generation of electrical energy is directly related to the performance of the generator used. In order to achieve the desired criteria for a generator design, many issues should be considered together. In order for this study to do, a 14‐pole and 5 kW permanent magnet synchronous generator (PMSG) was designed using the innovative optimizer named the weighted mean of vectors (INFO), the jumping spider optimization algorithm (JSOA), the teaching–learning‐based optimization (TLBO), the pelican optimization algorithm (POA) and the teaching‐learning‐studying‐based optimization (TLSBO) algorithms. The generator performance was optimized within the determined inequality constraints by the offset and embrace value and six parameters of the stator slot structure. The generator designed with the parameters determined by the TLSBO was more successful than the generators designed according to all the other proposed algorithms. The total harmonic distortion (THD) value decreased by 51.983% compared to the initial design at approximately the same efficiency.

Abstract Background In this research, an astute system has been developed by using machine learning and data mining approach to predict the risk level of cervical and ovarian cancer in association to stress. Results For functioning factors and subfactors, several machine learning models like Logistics Regression, Random Forest, AdaBoost, Naïve Bayes, Neural Network, kNN, CN2 rule Inducer, Decision Tree, Quadratic Classifier were compared with standard metrics e.g., F1, AUC, CA. For certainty info gain, gain ratio, gini index were revealed for both cervical and ovarian cancer. Attributes were ranked using different feature selection evaluators. Then the most significant analysis was made with the significant factors. Factors like children, age of first intercourse, age of husband, Pap test, age are the most significant factors of cervical cancer. On the other hand, genital area infection, pregnancy problems, use of drugs, abortion, and the number of children are important factors of ovarian cancer. Conclusion Resulting factors were merged, categorized, weighted according to their significance level. The categorized factors were indexed using ranker algorithm which provides them a weightage value. An algorithm has been formulated afterward which can be used to predict the risk level of cervical and ovarian cancer in relation to women's mental health. The research will have a great impact on the low incoming country like Bangladesh as most women in low incoming nations were unaware of it. As these two can be described as the most sensitive cancers to women, the development of the application from algorithm will also help to reduce women’s mental stress. More data and parameters will be added in future for research in this perspective.

PurposeTraditional library book recommendation methods are mainly based on association rules and user profiles. They may help to learn about students' interest in different types of books, e.g., students majoring in science and engineering tend to pay more attention to computer books. Nevertheless, most of them still need to identify users' interests accurately. To solve the problem, the authors propose a novel embedding-driven model called InFo, which refers to users' intrinsic interests and academic preferences to provide personalized library book recommendations.Design/methodology/approachThe authors analyze the characteristics and challenges in real library book recommendations and then propose a method considering feature interactions. Specifically, the authors leverage the attention unit to extract students' preferences for different categories of books from their borrowing history, after which we feed the unit into the Factorization Machine with other context-aware features to learn students' hybrid interests. The authors employ a convolution neural network to extract high-order correlations among feature maps which are obtained by the outer product between feature embeddings.FindingsThe authors evaluate the model by conducting experiments on a real-world dataset in one university. The results show that the model outperforms other state-of-the-art methods in terms of two metrics called Recall and NDCG.Research limitations/implicationsIt requires a specific data size to prevent overfitting during model training, and the proposed method may face the user/item cold-start challenge.Practical implicationsThe embedding-driven book recommendation model could be applied in real libraries to provide valuable recommendations based on readers' preferences.Originality/valueThe proposed method is a practical embedding-driven model that accurately captures diverse user preferences.

Labeling of groups and events describes how groups connected to religious, political or other forms of violence as well as their acts are labeled or evaluated. These labels might vary from more nominal descriptions (e.g., “gunmen”) to more judgmental descriptions (e.g., “terrorist”), leading to different perceptions of these groups and acts by the public. Field of application/theoretical foundation: Labels for groups and events are of interest in journalism research, political communication, research on terrorism and violence as well as stereotyping. These measurements are often based on “Social Identity Theory” (Brown, 2000) as a theoretical foundation for why some groups and events connected to violence are described in a negative way – i.e., as an out-group –, whilst others are described in a neutral way or even positively, i.e., as an in-group. References/combination with other methods of data collection: A study by Huff and Kertzer (2017) for example combines a conjoint experiment with an “Automated Content Analysis” of media coverage to understand how the public would label different acts of violence in comparison to the media. Two studies that have been particularly influential in studying the labeling of violent acts and perpetrators will be discussed in more detail in the following sections. Example studies: Nagar (2010); Weimann (1985) Information on Nagar, 2010 Author: Nagar Research question: How did American news media cover politically violent organizations that are not linked to Al Qaeda or the events of 9/11? Object of analysis: News coverage by two American newspapers (The New York Times, The Washington Post) Time frame of analysis: 1998–2004 Info about variables Variable name/definition: Media frame: “First, the labels that describe political violence were coded separately for each segment. Second, the article frame was determined based on the most frequent label.” (Nagar, 2010, p. 537) Level of analysis: Headline, lead paragraph, text Variables and values: four different label categories for labels in text: neutral (“rebel”, “rebellion”, “insurgent”, “insurgency”, “guerrilla”, “militant”, “combatants”, “revolt”, “uprising”, “revolutionary”, “paramilitaries”, “insurrection”, “separatist”), negative (“terror”, “terrorize”, “terrorist”, “terrorism”), positive (“freedom fighter”, “liberation movement”, “independence movement”), no label mentioned Reliability: Krippendorff’s alpha: .82 Information on Weimann, 1985 Authors: Weimann Research question: Which labels did the press use in referring to terrorists when covering terrorist attacks? Object of analysis: Israel’s major newspapers Time frame of analysis: 1979–1981 Info about variables Variable name/definition: Label Variables and values: three different labels categories for labels in text: negative (“murderers”, “saboteurs”, “assassins”, “separatists”), neutral (“guerillas”, “army”, “front”, “nationalists”, “underground”, “separatists”) and positive (“patriots”, “freedom fighters”, “liberation movement”, “liberation organization”) Reliability: not applicable Table 1. Measurement of “Labeling of Groups and Events” in terrorism coverage. Author(s) Sample Manifestations Reliability Codebook Boyle & Mower (2018) Newspaper articles Computer-assisted key-word search, looking up labels such as “terror” Not applicable Not available De Veen & Thomas (2020) Newspaper articles 3 different label categories: negative (“terrorist”, “racist”, “extremist”, “fundamentalist” and clear links to terrorist organizations such as ISIS), neutral (“perpetrator”, “shooter”, “attacker” or other labels emphasizing race and ethnicity, for example “Muslim” or “American”), or positive (family- or work-related labels such as “father” or “colleagues”) Not reported Not available Nagar (2010) Newspaper articles 4 different label categories: neutral (“rebel”, “rebellion”, “insurgent”, “insurgency”, “guerrilla”, “militant”, “combatants”, “revolt”, “uprising”, “revolutionary”, “paramilitaries”, “insurrection”, “separatist”), negative (“terror”, “terrorize”, “terrorist”, “terrorism”), positive (“freedom fighter”, “liberation movement”, “independence movement”), or no label mentioned Krippendorf’s alpha: .82 Available Picard & Adams (1987) Newspaper articles 2 different label categories: nominal (e.g., “attacker”) or descriptive (e.g., “radical”) Holsti: .98 Not available Samuel-Azran et al. (2015) Newspaper articles 7 different labels for perpetrators: “terrorist/Jewish terrorist”, “the Jewish terrorist”, “terror-accused”, “killer”, “mass murderer”, “serial stabber/criminal”, “other”; 9 different labels for act: “terror”, “massacre/mass murders”, “bombing/shooting”, “right wing crime”, “description assault (stabbing etc.)”, “criminal”, “attack”, “insanity”, “other” Scott’s pi indicating lowest value for any variable in the study: .86 Not available Simmons & Lowry (1990) Magazine articles 13 different labels for perpetrators: “terrorist”, “gunman”, “guerilla”, “attacker”, “extremist”, “radical”, “hijacker”, “revolutionary”, “nationalist”, “armed man/men”, “leftist”, “rightist”, “militiaman/militiamen” Not reported Available Weimann (1985) Newspaper articles 3 different labels categories for perpetrators: negative (“murderers”, “saboteurs”, “assassins”, “separatists”), neutral (“guerillas”, “army”, “front”, “nationalists”, “underground”, “separatists”), or positive (“patriots”, “freedom fighters”, “liberation movement”, “liberation organization”) Not applicable Not available References Boyle, K., & Mower, J. (2018). Framing terror: A content analysis of media frames used in covering ISIS. Newspaper Research Journal, 39(2), 205–219. doi:10.1177/0739532918775667 Brown, R. (2000). Social identity theory: past achievements, current problems and future challenges. European Journal of Social Psychology, 30(6), 745–778. De Veen, L., & Thomas, R. (2020). Shooting for neutrality? Analysing bias in terrorism reports in Dutch newspapers. Media, War & Conflict. Advance Online Publication. doi:10.1177/1750635220909407 Huff, C., & Kertzer, J.D. (2017). How the public defines terrorism. American Journal of Political Science, 62(1), 55-71. doi:10.1111/ajps.12329 Nagar, N. (2010). Who is afraid of the t-word? Labeling terror in the media coverage of political violence before and after 9/11. Studies in Conflict & Terrorism, 33(6), 533–547. doi:10.1080/10576101003752655 Picard, R. G., & Adams, P. D. (1987). Characterizations of acts and perpetrators of political violence in three elite U.S. daily newspapers. Political Communication, 4(1), 1–9. doi:10.1080/10584609.1987.9962803 Samuel-Azran, T., Lavie-Dinur, A., & Karniel, Y. (2015). Narratives used to portray in-group terrorists: A comparative analysis of the Israeli and Norwegian press. Media, War & Conflict, 8(1), 3–19. doi:10.1177/1750635214531106 Simmons, B. K., & Lowry, D. N. (1990). Terrorists in the news, as reflected in three news magazines, 1980–1988. Journalism Quarterly, 67(4), 692–696. doi:10.1177/107769909006700423 Weimann, G. (1985). Terrorists or freedom fighters? Labeling terrorism in the Israeli press. Political Communication, 2(4), 433–445. doi:10.1080/10584609.1985.9962776

Interactivity (or reciprocity) is a key dimension to assess the deliberative quality of online discussions. In quantitative content analyses, this dimension measures if participants engage in dialog with each other and refer to each other. Field of application/Theoretical foundation Most studies on online discussions draw on deliberative norms to measure the quality of their discourse (e.g., Esau et al., 2017; Friess et al., 2021; Rowe, 2015; Ziegele et al., 2020; Zimmermann, 2017). Deliberation is an important concept for the study of (political) online discussions (Ziegele et al., 2020). It focuses on a free and equal exchange of arguments to bridge social differences and legitimize political decisions (Dryzek et al., 2019; Fishkin, 1991, Habermas, 2015). Interactivity is a key dimension of deliberative quality, since deliberation is always a reciprocal and dialogical process (Goodin, 2000; Zimmermann, 2017). Participants engage in a dialogic exchange with each other, reflecting on other views and perspectives, and referring to each other (Friess et al., 2021; Ziegele et al., 2020). This reciprocal process includes both responding and listening (Barber, 1984; Graham, 2009). Interactivity is considered essential for desirable effects of deliberation such as learning, tolerance building and opinion change (Estlund & Landmore, 2018; Friess et al., 2021). References/Combination with other methods Besides quantitative content analyses, the (deliberative) quality of online discussions is examined with qualitative content analyses and discourse analyses (e.g., Graham & Witschge, 2003; Price & Capella, 2002). Furthermore, participants’ perceptions of the quality of online discussions are investigated with qualitative interviews (e.g., Engelke, 2019; Ziegele, 2016) or a combination of qualitative interviews and content analy­sis (Díaz Noci et al., 2012). Cross-references Interactivity is one of five dimensions of deliberative quality in this database written by the same author. Accordingly, there are overlaps with the entries on inclusivity, rationality, explicit civility, and storytelling regarding theoretical background, references/combinations with other methods, and some example studies. Information on Esau et al. (2017) Authors: Katharina Esau, Dennis Friess, & Christiane Eilders Research question: “How does platform design affect the level of deliberative quality?” (p. 323) Object of analysis: “We conducted a quantitative content analysis of user comments left in a news forum, on news websites, and on Facebook news pages concerning the same journalistic content on two topics […] A sample of news articles […] with related user comments, was drawn from the online platforms of four German news media […] The first step of the sampling process consisted of 18 news articles from which 3,341 comments were collected […] In the second step for each article, up to 100 sequential comments were randomly selected for content analysis, leading to a total sample of 1,801 comments (979 on Facebook, 591 on news websites, and 231 in the news forum)” (p. 331). Time frame of analysis: December 2015 Info about variables Level of analysis: individual comment Variables and reliability: see Table 1 Table 1: Variables and Reliability (Esau et al., 2017, pp. 332-333): Dimension Measure Definition RCA Cohen’s Kappa Reciprocity General engagement This measure captures whether a comment addresses another comment. .92 - Argumentative engagement This measure captures whether a comment addresses a specific argument made in another comment. .77 .542 Critical engagement This measure captures whether a comment is critical of another comment. .89 - n = 40; 12 coders Values: Dichotomous measures (yes, no) Information on Heinbach & Wilms (2022) Authors: Dominique Heinbach & Lena K. Wilms (Codebook by Dominique Heinbach, Marc Ziegele, & Lena K. Wilms) Research question: Which attributes differentiate moderated from unmoderated comments? Object of analysis: The quantitative content analysis was based on a stratified random sample of moderated and not moderated comments (N = 1.682) from the German online participation platform “#meinfernsehen202” [#myTV2021], a citizen participation platform to discuss the future of public broadcasting in Germany. Time frame of analysis: November 24, 2020 to March 3, 2021 Info about variables Level of analysis: User comment Variables and reliability: see Table 2 Table 2: Variables and reliability (Heinbach & Wilms, 2022) Dimension Measure Definition Krippendorff’s α Reciprocity Reference to other users or to the community Does the comment refer to at least one other user, a group of users, or all users in the community? .78 Reference to the content of other comments Does the comment refer to content, arguments or positions in other comments? .78 Critical reference Does the comment refer to other comments in a critical manner? .86 n = 159, 3 coders Values: All variables were coded on a four-point scale (1 = clearly not present; 2 = rather not present; 3 = rather present; 4 = clearly present). Detailed explanations and examples for each value are provided in the Codebook (in German). Codebook: in the appendix of this entry (in German) Information on Stromer-Galley (2007) Author: Jennifer Stromer-Galley Research question: The aim of the paper was developing a coding scheme for academics and practitioners of deliberation to systematically measure what happens during group deliberations (p. 1; p. 7). Object of analysis: The author conducted a secondary analysis of online group discussions (23 groups with 5-12 participants) in an experiment called “The Virtual Agora Project” at Carnegie Mellon Unversitiy in Pittsburgh, Pennsylvania. Participants attended the discussions from dormitory rooms that were equipped with a computer, headphones, and microphone. The group discussions were recorded and transcribed for analysis (pp. 7-8). Although strictly speaking the study does not analyze media content, the coding scheme has provided the basis for numerous other studies on the deliberative quality of online discussions (e.g., Rowe, 2015; Stroud et al., 2015; Ziegele et al., 2020). Time frame of analysis: Three weeks in July 2004 (p. 7). Info about variables Level of analysis: Level of the turn: Speaking contribution of a participant. Participants had to get “in line” to speak. When a speaker had finished their turn, the software activated the next speaker (max. 3 minutes per turn) (p. 8). Level of the thought: Coders segmented each turn into thought units before coding the categories. “A thought is defined as an utterance (from a single sentence to multiple sentences) that expresses an idea on a topic. A change in topic signaled a change in thought. A second indicator of a change in thought was a change in the type of talk. The distinct types of talk that this coding captured were the following: talk about the problem of public schools, talk about the process of the talk, talk about the process of the deliberation, and social talk” (p. 9). Variables an values: see Table 3 Reliability: “Two coders spent nearly two months developing and training with the coding scheme. The intercoder agreement measures […] were established from coding 3 of the 23 groups, which were randomly selected. […] Cohen’s Kappas of the coding elements described above are as follows: thought statements on the problem of public schools, .95; […] turn type (new topic, continuing self, responding to others) .97; meta-talk, 1.0 […]” (p. 13-14). Codebook: in the appendix (pp. 22-33) Table 3: Variables and values of the dimension “engagement” (Stromer-Galley, 2007, p.12; pp. 24-26). Category Level Description Value Definition Turn-type Turn Identify whether and to whom this turn is referring. Starting a new topic A new topic (not prompted by the moderator). Respond on topic A turn that is in response to a prior speaker or is on a topic that has been discussed. Includes responding to multiple speakers. Respond to moderator A turn that is a response to a prompt or question from the moderator. Continue self A turn that seems not to respond to anything a prior speaker said but to continue the current speaker’s ideas from one of his or her prior turns. Problem Thought Talk about the problem is talk that focuses on the issue under consideration. Question A genuine question directed to another speaker that is trying to seek information or an opinion from others. Metatalk Thought Metatalk is talk about the talk. It attempts to step back and assess what has transpired or is transpiring in the interaction. Consensus Consensus metatalk is talk about the speaker’s sense of consensus of the group (“I think we all agree that . . . .”), including an explanation for the collective’s opinions or the collective’s behavior (We’re asking you these questions because . .). Conflict Highlighting some disagreement or conflict in the group (“I sense some disagreement around . . . .”). Clarify own Clarify the speaker’s own opinion or fact statement (“what I’m trying to say is”). It’s an attempt to clarify what the speaker means. This will arise ONLY after they’ve provided an opinion, NOT a question, and are now trying to clarify their original opinion on the problem, likely because they believe someone has misunderstood them. Clarify other Clarify someone else’s argument/opinion or fact statement (“Sally, so, what you’re saying is . . . “). It is an attempt to clarify what someone else means. Pay attention to the use of another participants’ name. That can be a sign of metatalk of another’s position. Example studies Esau, K., Fleuß, D. & Nienhaus, S.‑M. (2021). Different Arenas, Different Deliberative Quality? Using a Systemic Framework to Evaluate Online Deliberation on Immigration Policy in Germany. Policy & Internet, 13(1), 86–112. https://doi.org/10.1002/poi3.232 Esau, K., Friess, D. & Eilders, C. (2017). Design Matters! An Empirical Analysis of Online Deliberation on Different News Platforms. Policy & Internet, 9(3), 321–342. https://doi.org/10.1002/poi3.154 Esau, K., Frieß, D. & Eilders, C. (2019). Online-Partizipation jenseits klassischer Deliberation: Eine Analyse zum Verhältnis unterschiedlicher Deliberationskonzepte in Nutzerkommentaren auf Facebook-Nachrichtenseiten und Beteiligungsplattformen. In I. Engelmann, M. Legrand & H. Marzinkowski (Hrsg.), Digital Communication Research: Bd. 6. Politische Partizipation im Medienwandel (S. 221–245). Friess, D., Ziegele, M. & Heinbach, D. (2021). Collective Civic Moderation for Deliberation? Exploring the Links between Citizens’ Organized Engagement in Comment Sections and the Deliberative Quality of Online Discussions. Political Communication, 38(5), 624–646. https://doi.org/10.1080/10584609.2020.1830322 Heinbach, D. & Wilms, L. K. (2022): Der Einsatz von Moderation bei #meinfernsehen2021 [The deployment of moderation at #meinfernsehen2021]. In: F. Gerlach, C. Eilders & K. Schmitz (Eds.): #meinfernsehen2021. Partizipationsverfahren zur Zukunft des öffentlich-rechtlichen Fernsehens. Baden-Baden: Nomos. Rowe, I. (2015). Deliberation 2.0: Comparing the Deliberative Quality of Online News User Comments Across Platforms. Journal of Broadcasting & Electronic Media, 59(4), 539–555. https://doi.org/10.1080/08838151.2015.1093482 Stromer Galley, J. (2007). Measuring Deliberation's Content: A Coding Scheme. Journal of Public Deliberation, 3(1), Article 12. Ziegele, M., Quiring, O., Esau, K. & Friess, D. (2020). Linking News Value Theory With Online Deliberation: How News Factors and Illustration Factors in News Articles Affect the Deliberative Quality of User Discussions in SNS’ Comment Sections. Communication Research, 47(6), 860-890. https://doi.org/10.1177/0093650218797884 Zimmermann, T. (2017). Digitale Diskussionen: Über politische Partizipation mittels Online-Leserkommentaren. Edition Politik: Bd. 44. transcript Verlag. http://www.content-select.com/index.php?id=bib_view&ean=9783839438886 Further references Barber, B. R. (1984). Strong democracy: Participatory politics for a new age. University of California Press. Díaz Noci, J., Domingo, D., Masip, P., Micó, J. L. & Ruiz, C. (2012). Comments in news, democracy booster or journalistic night­mare: Assessing the quality and dynamics of citizen debates in Catalan online new­spapers. #ISOJ, 2(1), 46–64. https://isoj.org/ wp-content/uploads/2016/10/ISOJ_Jour­nal_V2_N1_2012_Spring.pdf#page=46 Dryzek, J. S., Bächtiger, A., Chambers, S., Cohen, J., Druckman, J. N., Felicetti, A., Fishkin, J. S., Farrell, D. M., Fung, A., Gutmann, A., Landemore, H., Mansbridge, J., Marien, S., Neblo, M. A., Niemeyer, S., Setälä, M., Slothuus, R., Suiter, J., Thompson, D. & Warren, M. E. (2019). The crisis of democracy and the science of deliberation. Science (New York, N.Y.), 363(6432), 1144–1146. https://doi.org/10.1126/science.aaw2694 Engelke, K. M. (2019). Enriching the Conversation: Audience Perspectives on the Deliberative Nature and Potential of User Comments for News Media. Digital Journalism, 8(4), 1–20. https://doi.org/10.1080/21670811.2019.1680567 Estlund, D. & Landemore, H. (2018). The epistemic value of democratic deliberation. In A. Bächtiger, J. S. Dryzek, J. J. Mansbridge & M. E. Warren (Hrsg.), Oxford handbooks online. The Oxford handbook of deliberative democracy: An introduction (S. 113–131). Oxford University Press. Fishkin, J. S. (1991). Democracy and deliberation: New directions for democratic reform. Yale University Press. http://www.jstor.org/stable/10.2307/j.ctt1dt006v https://doi.org/10.2307/j.ctt1dt006v Goodin, R. E. (2000). Democratic Deliberation Within. Philosophy & Public Affairs, 29(1), 81–109. https://doi.org/10.1111/j.1088-4963.2000.00081.x Graham, T. (2009). What's Wife Swap got to do with it? Talking politics in the net-based public sphere Amsterdam: University of Amsterdam DOI: 10.13140/RG.2.1.3413.0088 Graham, T. & Witschge, T. (2003). In Search of Online Deliberation: Towards a New Method for Examining the Quality of Online Discussions. Communications, 28(2). https://doi.org/10.1515/comm.2003.012 Habermas, J. (2015). Between facts and norms: Contributions to a discourse theory of law and democracy (Reprinted.). Polity Press. Price, V. & Cappella, J. N. (2002). Online deliberation and its influence: The Electronic Dialogue Project in Campaign 2000. IT&Society, 1(1), 303–329. https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.9.5945&rep=rep1&type=pdf Stroud, N. J., Scacco, J. M., Muddiman, A., & Curry, A. L. (2015). Changing Deliberative Norms on News Organizations' Facebook Sites. Journal of Computer-Mediated Communication, 20(2), 188–203. https://doi.org/10.1111/jcc4.12104 Ziegele, M. (2016). Nutzerkommentare als Anschlusskommunikation: Theorie und qualitative Analyse des Diskussionswerts von Online-Nachrichten [The Discussion Value of Online News. An Analysis of User Comments on News Platforms]. Springer VS.

“We may no longer be able to trust technology. A computer program could, without warning, become an uncontrollable force, triggered by a date, an event or a timer.” (Clough and Mungo 223) Introduction In 1991 the Information Security Handbook noted how “society is becoming increasingly dependent on the accurate and timely distribution of information” (Shain 4). This dependence, however, exposed the society to new kinds of dangers, accidents that have to do with information disorders – viruses, worms, bugs, malicious hackers etc. In this essay, I focus on digital viruses as disorderly elements within the digital culture. It is due to certain key principles in computing and computer security that viruses and worms have acquired their contemporary status as malicious software, that is, malware – elements of chaos, accident and disorder. According to my claim, the fear of viruses does not stem just from the contemporary culture of digital technology. It is part of a longer genealogy of modern computing, which has emphasized issues of control, reliability and order. Viruses and worms threaten the conceptual ontology of digital culture in a similar fashion as epidemic diseases have been figures for social disorder throughout Western history. Unlike AIDS or other deadly biological viruses, computer viruses have not been known to cause casualties to humans, yet they have been treated the last years as the “killer viruses of digital culture”, connotating the seriousness of the threat. A “viral perspective” to digital culture reveals how underlying articulations of order are used to construct an all-too-harmonious picture of computers in modern society. Reliability Anti-virus manuals, guidebooks and other such publications have especially contributed to our understanding of viruses as threats to the orderly digital society. The editorial of the first issue of Virus Bulletin (July 1989) sees viruses as a cunning form of vandalism and an indication of ”sabotage mentality”. Viruses destroy information and produce uncontrollability: Rather like Hitler’s V1 ‘flying bomb’, no-one knows when or where a computer virus will strike. They attack indiscriminately. Virus writers, whether or not they have targeted specific companies or individuals, must know that their programs, once unleashed, soon become uncontrollable. (Virus Bulletin 2) Computer viruses mean unreliable and unexpected danger: they are a chaotic element within a system based on security and order. According to a widely embraced view computer security means 1) confidentiality (the privacy of sensitive information), 2) integrity (authorized information and program exchange) and 3) availability (systems work promptly and allow access to authorized users). (E.g. Shain 5). Viruses and other forms of malicious code are, consequently, a direct threat to these values, part of the modern episteme in general. This is what I will here define as “a computational way of thinking”. The concept refers not only to the epistemological and ontological presuppositions in actual computer science discussions, but also to the larger cultural historical contexts surrounding the design, implementation and use of computers. Of course, one has to note that computers have never been those reliable and rational dream-machines they have been taken to be, as they are exposed to various potentials for breaking down of which viruses and worms form only a minor part. Yet, interestingly, reading professional and popular depictions of digital viruses reveals that these sources do consider computers as otherwise integrated, coherent and pristine machines of rationality, which are only temporarily disturbed by the evil occurrences of external malicious software. Control The virus researcher Vesselin Bontchev acknowledges how issues of trust and control are at the heart of computing and the virus threat: “a computer virus steals the control of the computer from the user. The virus activity ruins the trust that the user has in his/her machine, because it causes the user to lose his or her belief that she or he can control this machine” (31). This definition resonates with broader cultural trends of modernization. Zygmunt Bauman has expressed the essence of modern science as an ”ambition to conquer Nature and subordinate it to human needs” (39). Bauman understands this as ”control management”: the moulding of things to suit human needs. The essence of modern technology proceeds along the same lines, defined through values of progress, controllability, subordination of chaos and reification of the world. From the 19th-century on, technology became closely associated with advances in science. The values of order and control were embedded in the machines and technological systems, and with time, these values became the characteristics of modern technological culture. In this vein modernity can be defined as a new attitude towards controlling information. Capitalism and digital culture as historical phenomena share the valuation of abstraction, standardization and mechanization, which were already part of the technological culture of the 19th-century. Similarly, Turing’s universal machine was above all a machine of ordering and translation, with which heterogenous phenomena could be equated. This idea, concretised in typewriters, conveyer belts, assembly lines, calculators and computers served the basis for both digital machines and capitalism. The concrete connection was the capitalist need to control the increasingly complex amount of production, circulation and signs. Rationalism – as exemplified in Babbage’s differential calculators, Taylor’s ideas of work-management and cybernetics – was the image of thought incorporated in these machines (Gere 19–40). Rationalism In general, first order cybernetics fulfilled the project of modern abstract rationalism. In other words, notions of control and order play a significant role in the archaeology of information technological security, and these themes are especially visible in the thinking of Norbert Wiener, the pioneer of cybernetics. Wiener’s cybernetics touches, most of all, upon the question of understanding the world as communication circuits and controlling them via successful feedback loops that maintain the stasis of a system. This theory relates closely the problem of entropy, a classical notion in statistical mechanics from the 19th-century: “Just as the amount of information in a system is a measure of its degree of organization, so the entropy of a system is a measure of its degree of disorganization; and the one is simply the negative of the other” (Wiener 11). Wiener and the modern era share a respect for control and security. As products of modernity, cybernetics, systems theory and information theory are all in a way theories of order and cleanliness. This is the main theme of Stephen Pfohl’s essay “The Cybernetic Delirium of Norbert Wiener”, in which he describes the cultural historical background of modern cybernetic culture. To Pfohl, cybernetics does not mean a purely academic discipline but “a term connoting the most far-reaching of ultramodern forms of social control.” Pfohl delineates the genealogy of cybernetics from the early projects on anti-aircraft artillery to the functioning of the contemporary capitalist media culture. For Pfohl, Wiener’s theories connect directly to the power structures of modern society, sacrificing other ways of being, restricting other possible worlds from emerging. Paraphrasing Pfohl, cybernetics regulates and modifies the dynamic flows of the world into fixed, stabilized and controlled boundaries. Noise The engineering problem of logical calculation and communication of signals without noise expands towards the more general cultural fields of power and articulation. I would especially like to pick up the notion of noise, which, as understood by Bauman, means undefinability, incoherence, incongruity, incompatibility, illogicality, irrationality, ambiguity, confusion, undecidability, ambivalence, all tropes of “the other of order” (7). For cybernetics and early computer pioneers, noise meant a managing problem, objects in the way of transmitting signals. Noise as the most important problem for the rise of modern discourse networks was not solved once and for all in any historical phase, but remained part of the communication acts ever since, and the only resolution to the problem of non-communication was to incorporate it within the system (Kittler 242). Computer viruses can be understood as contemporary instances of this notion of noise. They are software that short-circuit the “normal” operations of a computer and connect themselves to the basic functioning of the machine. Viruses mean short-term wiring of noise to the components of a computer. By definition, viruses have been conceived as a threat to any computer system for a) virus activity is always uncontrollable, because the actions of the virus program are autonomous and b) viruses behave indeterminately and unpredictably (Lamacka 195). In a much more positive vein, this coupling of computing order and viral disorder has been noted by recent net art projects. According to the net artist Jaromil the digital domain produces a form of chaos – which is inconvenient because it is unusual and fertile – on which people can surf. In that chaos, viruses are spontaneous compositions which are like lyrical poems in causing imperfections in machines ”made to work” and in representing the rebellion of our digital serfs. Jaromil takes noise as the starting point and articulates how viruses function also as forms of resistance to the contemporary informational capitalist ideology of the digital. Charlie Gere’s analysis of the connections between modern technology and capitalism is apt in this regard as well: the abstract, standardizing and mechanizing machines of modernization serve the basis for both the cult of the digital and contemporary capitalism in a way that makes these two almost siblings. Thus, also accidents of this techno-capitalist culture are not solely technical, but social in that they are articulated on a plane of society and cultural interaction. Viruses can thus be understood as those “unwanted bads” that are a by-product of post-industrial culture of production of goods (Van Loon), as well as they can be viewed alongside other mass mediated apocalyptic monsters threatening the order of contemporary Western culture, as Luca Lampo from the net art group _[epidemiC]_ suggests: We feel that “The Virus” is the “stranger”, the “other”, in our machine, a sort of digital sans papier—uncontrollable diversity. Once Hollywood, like Empire, finished killing “Indians” and the “Soviet Russians”, the Hollywood propaganda machine had to build other anti-Empire monsters to keep alive the social imaginary of 2001: aliens, meteors, epidemic… so many monsters. In this light, while being technical bits of code that from time to time cause trouble for users, viruses act also as social signs which can be activated in various contexts. For representatives of the official computer culture viruses and worms are signs of disorder, chaos and crime that undermine the presumed reliability of digital culture, which would otherwise function “normally.” Yet, according to some commentators, viral disorder should not mean solely anarchy but a space for variation and experimentation that resist the one-way ideology of computer rationalism. (See Sampson; Cohen; Deleuze.) For some, that ideology has been crystallized in the figure of Microsoft, a popular target for virus attacks. This view accentuates that the genealogy of computers and rationalism analysed above is but one potential history. There is always the possibility to write the counter-memory of the disorderly, accidental, probabilistic and contingent nature of technological culture. Hence, viruses might prove out to be also intellectual tools, with which to create new concepts and viewpoints to digital culture and the cultural history of computing and technology in general. Already Martin Heidegger (§ 16) proposed that modern technology reveals itself at the moment of its breaking. In this sense, viruses reveal the functioning of a certain ideological or micro-political constitution of digital order. The challenge is not to take any notion of a “healthy” cultural network without disturbances as the starting point, but to see elements of break-up as part and parcel of those systems. Even if we are used to thinking of systems as orderly and harmonious, “[i]n the beginning there was noise”, as Serres (13) notes. This emphasizes the conceptual space we should give to the parasites who reveal the networks of power that otherwise are left unnoticed. References Bauman, Zygmunt. Modernity and Ambivalence. Cambridge: Polity Press, 1995 Bontchev, Vesselin. “Are ‘Good’ Computer Viruses Still a Bad Idea?” EICAR Conference Proceedings 1994, 25–47. Clough, Bryan and Mungo, Paul. Approaching Zero: Data Crime and the Computer Underworld. London & Boston: Faber & Faber, 1992. Cohen, Fred. It’s Alive! The New Breed of Living Computer Programs. New York: John Wiley & Sons, 1994. Deleuze, Gilles. “Post-scriptum sur les sociétés de contrôle” In: Pourparlers 1972–1990. Paris: Les éditions de minuit, 1990, 240–7. Gere, Charlie. Digital Culture. London: Reaktion Books, 2002. Heidegger, Martin. Being and Time. Albany: New York University Press, 1996. Jaromil. “:(){ :|:& };:” ‘I love You’ – exhibition catalogue, 2002, http://www.digitalcraft.org/index.php?artikel_id=292> Kittler, Friedrich. Draculas Vermächtnis: Technische Schriften. Leipzig: Reclam Verlag Leipzig, 1993. Lamacka, Pavel. “Harmless and useful viruses can hardly exist.” Virus Bulletin Conference Proceedings 1995, 193–8. Lampo, Luca. “When The Virus Becomes Epidemic.” An Interview with Luca Lampo by Snafu and Vanni Brusadin, 18.4.2002, http://www.epidemic.ws/downJones_press/THE_THING_ Interview_files/index_files/display.forum> Pfohl, Stephen. “The Cybernetic Delirium of Norbert Wiener.” C-Theory 30.1.1997 http://www.ctheory.net/text_file.asp?pick=86>. Sampson, Tony. ”A Virus in Info-Space.” M/C Journal http://www.media-culture.org.au/0406/07_Sampson.html>. Serres, Michel. The Parasite. Baltimore & London: The Johns Hopkins University Press, 1982. Shain, Michael. ”An Overview of Security”. Information Security Handbook. Eds. Michael Caelli, Dennis Longley & Michael Shain. Basingstoke: Macmillan, 1994 (1991). Van Loon, Joost. Risk and Technological Culture: Towards a Sociology of Virulence. London & New York: Routledge, 2002. Virus Bulletin, “Editorial”, July 1989. Wiener, Norbert. Cybernetics, or Control and Communication in the Animal and the Machine. 2nd edition. (1st edition 1948). New York & London: The M.I.T. Press and John Wiley & Sons, 1961. Citation reference for this article MLA Style Parikka, Jussi. "Viral Noise and the (Dis)Order of the Digital Culture." M/C Journal 7.6 (2005). echo date('d M. Y'); ?> <http://journal.media-culture.org.au/0501/05-parikka.php>. APA Style Parikka, J. (Jan. 2005) "Viral Noise and the (Dis)Order of the Digital Culture," M/C Journal, 7(6). Retrieved echo date('d M. Y'); ?> from <http://journal.media-culture.org.au/0501/05-parikka.php>.

Explicit civility or respect is a key dimension to assess the (deliberative) quality of online discussions. In contrast to operationalizations that address civility through the mere absence of incivility or offensive language, this construct measures explicit indicators for respect, such as acknowledgements, endorsement, and explicit valuation. Field of application/Theoretical foundation Most studies on online discussions draw on deliberative norms to measure the quality of their discourse (e.g., Esau et al., 2017; Friess et al., 2021; Rowe, 2015; Ziegele et al., 2020; Zimmermann, 2017). Deliberation is an important concept for the study of (political) online discussions and consists of a fair and respectful exchange of arguments between participants who are deemed as equals (Graham & Witschge, 2003; Ziegele et al., 2020). Mutual respect and appreciation of one another are considered fundamental assets of a democratic society (Papacharissi, 2004). A minimum level of respect ensures the mutual acknowledgement of participants as free and equal members of society and hence is a requirement for deliberation (Habermas, 2007; Steiner, 2012; Ziegele et al., 2020). References/Combination with other methods Besides quantitative content analyses, the (deliberative) quality of online discussions is examined with qualitative content analyses and discourse analyses (Graham & Witschge, 2003; Price & Capella, 2002). Furthermore, perceptions of civility and incivility are investigated with qualitative interviews and focus groups (Bormann, 2022; Engelke, 2019; Ziegele, 2016), surveys (Kenski et al., 2020; Stryker et al., 2016) and experimental designs (Muddiman, 2017; Ziegele et al., 2019). Cross-references Explicit civility is one of five dimensions of deliberative quality in this database written by the same author. Accordingly, there are overlaps with the entries on interactivity, inclusivity, rationality, and storytelling regarding theoretical background, references/combinations with other methods, and some example studies. Information on Heinbach & Wilms (2022) Authors: Dominique Heinbach & Lena K. Wilms (Codebook by Dominique Heinbach, Marc Ziegele, & Lena K. Wilms) Research question: Which attributes differentiate moderated from unmoderated comments? Object of analysis: The quantitative content analysis was based on a stratified random sample of moderated and not moderated comments (N = 1.682) from the German online participation platform “#meinfernsehen2021” [#myTV2021], a citizen participation platform to discuss the future of public broadcasting in Germany. Time frame of analysis: November 24, 2020 to March 3, 2021 Info about variables Level of analysis: User comment Variables and reliability: see Table 1 Values: All variables were coded on a four-point scale (1 = clearly not present; 2 = rather not present; 3 = rather present; 4 = clearly present). Detailed explanations and examples for each value are provided in the Codebook (in German). Codebook: in the appendix of this entry (in German) Table 1: Variables and reliability (Heinbach & Wilms, 2022) Dimension Measure Definition Krippendorff’s α (n = 159, 3 coders) Explicit respect Polite salutation Does the comment contain formulations of polite salutations, greetings or farewell phrases, e.g., “Dear …”, “Have a good weekend”? .80 Expression of respect Does the comment contain appreciation, approval, praise, or acknowledgements, e.g, “Kudos!”, “You are doing a great job, “Thank you”, “I respect your opinion“? .71 Information on Stromer-Galley (2007) Author: Jennifer Stromer-Galley Research question: The aim of the paper was developing a coding scheme for academics and practitioners of deliberation to systematically measure what happens during group deliberations (p. 1; p. 7). Object of analysis: The author conducted a secondary analysis of online group discussions (23 groups with 5-12 participants) in an experiment called “The Virtual Agora Project” at Carnegie Mellon Unversitiy in Pittsburgh, Pennsylvania. Participants attended the discussions from dormitory rooms that were equipped with a computer, headphones, and microphone. The group discussions were recorded and transcribed for analysis (pp. 7-8). Although strictly speaking the study does not analyze media content, the coding scheme has provided the basis for numerous other studies on the deliberative quality of online discussions (e.g., Rowe, 2015; Stroud et al., 2015; Ziegele et al., 2020). Time frame of analysis: Three weeks in July 2004 (p. 7). Info about variables Level of analysis: Social talk was measured on the level of the thought. Coders segmented each speaking contribution into thought units before coding the categories. “A thought is defined as an utterance (from a single sentence to multiple sentences) that expresses an idea on a topic. A change in topic signaled a change in thought. A second indicator of a change in thought was a change in the type of talk. The distinct types of talk that this coding captured were the following: talk about the problem of public schools, talk about the process of the talk, talk about the process of the deliberation, and social talk” (p. 9). Variables and values: see Table 2 Reliability: Reliability scores for social talk are not provided. Codebook: in the appendix (pp. 22-33) Table 2: Variables and values (Stromer-Galley, 2007, p. 9; pp. 26-27). Variable Description Value Definition Social talk Social talk is talk that brings the strangers together by building social bonds, including salutations, praise, and apologies. Salutations Statements of welcome, greeting, hello, and good bye, see you later, and the like. Apologies Statements of apology: I’m sorry, and ‘I hope’ statements, such as “I hope I haven’t been too obnoxious.” Includes statements of reflection of how the participant performed in the group (likely comes at the end of the group’s discussion): “I hope my few ideas did get across.” Praise Includes thank you, you’re welcome, as well as praise for other individuals or the group (“you’ve been a good group.” I’ve really enjoyed myself,” “this has been fun”) Praise in the service of an argument about the problem is coded as a problem thought (“I want to commend Sally for volunteering at her school. We need more people to be volunteers”). ChitChat Thought statements that are not on topic relative to the deliberation. These could be jokes or puns (but not as they relate to the problem of schools), social chit chat about the weather, and the like. Information on Zimmermann (2017) Author: Tobias Zimmermann Research question: Which role do online reader comments play for a deliberative-democratic understanding of a digital public sphere? (p. 11) Object of analysis: To compare discursive participation online and offline, the author conducted a full-sample content analysis of online reader comments (N = 1.176) and letters to the editor (N = 381) from German local newspapers on three similar conflicts in local politics concerning the renaming of streets and squares. Because the coding scheme was based on the discourse quality index (DQI), only contributions that contained a demand were included in the analysis, that is, “a proposal on what decision should or should not be made” Steenbergen et al., 2003, p. 27). Only then, a speech act is considered relevant from a discourse ethics perspective. Time frame of analysis: June 2012 to May 2013 Info about variables Variables: For the variable respect towards groups, the author extends the respect variable of the Discourse Quality Index (DQI, Steenbergen et al., 2003) by adding anti-democratic behavior following Papacharissi (2004). Besides the ordinal variable “respect”, the author measured the dichotomous variable “democratic respect”. Level of analysis: Individual contribution Variables and values: see Table 3 Reliability: Intracoder reliability was tested on a subset of 100 comments. The ordinal respect variable exceeded a Krippendorff’s Alpha above .73 (p. 201). The dichotomous variable “democratic respect” that measured if a comment contained anti-democratic behavior or not reached a Krippendorff’s Alpha of .89 (p. 200-201). Codebook: pp. 159-185 (in German) Table 3: Variables and values (Zimmermann, 2017, p. 171; p. 189) Variable Value Definition Respect Anti-democratic behavior Only or predominantly statements are made that either contain at least one threat against the democratic system as a whole, use negative stereotypes, or question other individuals’ individual liberty rights. No respect This category applies when exclusively or predominantly negative statements about others, but not anti-democratic statements are made. Implicit respect There are no explicitly positive or negative statements to others, that is, a comment is neither explicitly respectful nor disrespectful. Balanced respect Both positive and negative statements in relation to others are expressed in the same degree. Explicit respect This category is applied when there is at least one explicitly positive statement regarding others and no negative statements, or if the positive statement clearly dominates the negative. Democratic respect Anti-democratic behavior Only or predominantly statements are made that either contain at least one threat against the democratic system as a whole, use negative stereotypes, or question other individuals’ individual liberty rights. Democratic respect Anti-democratic behavior does not occur. Example studies Heinbach, D. & Wilms, L. K. (2022): Der Einsatz von Moderation bei #meinfernsehen2021 [The deployment of moderation at #meinfernsehen2021]. In: F. Gerlach, C. Eilders & K. Schmitz (Eds.): #meinfernsehen2021. Partizipationsverfahren zur Zukunft des öffentlich-rechtlichen Fernsehens. Baden-Baden: Nomos. Stromer Galley, J. (2007). Measuring Deliberation's Content: A Coding Scheme. Journal of Public Deliberation, 3(1), Article 12. Zimmermann, T. (2017). Digitale Diskussionen: Über politische Partizipation mittels Online-Leserkommentaren [Digital discussions: On political participation trough online reader comments]. Edition Politik: Bd. 44. transcript Verlag. http://www.content-select.com/index.php?id=bib_view&ean=9783839438886 Further references Bormann, M. (2022). Perceptions and Evaluations of Incivility in Public Online Discussions—Insights From Focus Groups With Different Online Actors. Frontiers in Political Science, 4, Article 812145. https://doi.org/10.3389/fpos.2022.812145 Engelke, K. M. (2019). Enriching the Conversation: Audience Perspectives on the Deliberative Nature and Potential of User Comments for News Media. Digital Journalism, 8(4), 1–20. https://doi.org/10.1080/21670811.2019.1680567 Esau, K., Friess, D. & Eilders, C. (2017). Design Matters! An Empirical Analysis of Online Deliberation on Different News Platforms. Policy & Internet, 9(3), 321–342. https://doi.org/10.1002/poi3.154 Friess, D., Ziegele, M. & Heinbach, D. (2021). Collective Civic Moderation for Deliberation? Exploring the Links between Citizens’ Organized Engagement in Comment Sections and the Deliberative Quality of Online Discussions. Political Communication, 38(5), 624–646. https://doi.org/10.1080/10584609.2020.1830322 Graham, T. & Witschge, T. (2003). In Search of Online Deliberation: Towards a New Method for Examining the Quality of Online Discussions. Communications, 28(2). https://doi.org/10.1515/comm.2003.012 Habermas, J. (2007). Moral consciousness and communicative action (Repr). Polity. Kenski, K., Coe, K. & Rains, S. A. (2020). Perceptions of Uncivil Discourse Online: An Examination of Types and Predictors: An examination of types and predictors. Communication Research, 47(6), 795–814. https://doi.org/10.1177/0093650217699933 Muddiman, A. (2017). Personal and Public Levels of Political Incivility. International Journal of Communication, 11, 3182–3202. Papacharissi, Z. (2004). Democracy online: civility, politeness, and the democratic potential of online political discussion groups. new media & society, 6(2), 259–283. https://doi.org/10.1177/1461444804041444 Price, V. & Cappella, J. N. (2002). Online deliberation and its influence: The Electronic Dialogue Project in Campaign 2000. IT&Society, 1(1), 303–329. https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.9.5945&rep=rep1&type=pdf Rowe, I. (2015). Deliberation 2.0: Comparing the Deliberative Quality of Online News User Comments Across Platforms. Journal of Broadcasting & Electronic Media, 59(4), 539–555. https://doi.org/10.1080/08838151.2015.1093482 Steenbergen, M. R., Bächtiger, A., Spörndli, M., & Steiner, J. (2003). Measuring Political Deliberation: A Discourse Quality Index. Comparative European Politics, 1(1), 21–48. https://doi.org/10.1057/palgrave.cep.6110002 Steiner, J. (2012). The Foundations of Deliberative Democracy. Cambridge University Press. https://doi.org/10.1017/CBO9781139057486 Stroud, N. J., Scacco, J. M., Muddiman, A., & Curry, A. L. (2015). Changing Deliberative Norms on News Organizations' Facebook Sites. Journal of Computer-Mediated Communication, 20(2), 188–203. https://doi.org/10.1111/jcc4.12104 Stryker, R., Conway, B. A. & Danielson, J. T. (2016). What is political incivility? Communication Monographs, 83(4), 535–556. https://doi.org/10.1080/03637751.2016.1201207 Ziegele, M. (2016). Nutzerkommentare als Anschlusskommunikation: Theorie und qualitative Analyse des Diskussionswerts von Online-Nachrichten [The Discussion Value of Online News. An Analysis of User Comments on News Platforms]. Springer VS. Ziegele, M., Naab, T. K. & Jost, P. (2020). Lonely together? Identifying the determinants of collective corrective action against uncivil comments. New Media & Society, 22(5), 731-751. https://doi.org/10.1177/1461444819870130 Ziegele, M., Quiring, O., Esau, K. & Friess, D. (2020). Linking News Value Theory With Online Deliberation: How News Factors and Illustration Factors in News Articles Affect the Deliberative Quality of User Discussions in SNS’ Comment Sections. Communication Research, 47(6), 860-890. https://doi.org/10.1177/0093650218797884

Inclusivity is a key dimension to assess the deliberative quality of online discussions. In quantitative content analyses, this dimension measures the openness and accessibility of and the equality and diversity within a discussion. Field of application/Theoretical foundation Most studies on online discussions draw on deliberative norms to measure the quality of their discourse (e.g., Esau et al., 2017; Friess et al., 2021; Rowe, 2015; Ziegele et al., 2020; Zimmermann, 2017). Deliberation is an important concept for the study of (political) online discussions (Ziegele et al., 2020). It focuses on a free and equal exchange of arguments to bridge social differences and legitimize political decisions (Dryzek et al., 2019; Fishkin, 1991, Habermas, 2015). Inclusivity or open participation is one of the central criteria of Habermas’ discourse ethics. Deliberative discussions should be open to everyone and all participants should be able to express their attitudes, desires, and needs (Habermas, 2015; Steenbergen et al., 2003). Inclusivity occurs on two levels: On the one hand, it is a matter of open and free access for all citizens, which precedes the actual discussion process (input, Friess & Eilders, 2015). This precondition is often referred to as universalism or openness (Engelke, 2019; Kersting, 2008). In the discussion process itself (troughput, Friess & Eilders, 2015), all voices should have an equal opportunity to be heard and responded to, regardless of factors such as gender, race, or social background. Inclusivity usually implies opinion diversity, since one-sided discussions carry the risk of marginalizing other positions (Habermas, 2006; Manin, 1987; Zimmermann, 2017). References/Combination with other methods Besides quantitative content analyses, the (deliberative) quality of online discussions is examined with qualitative content analyses and discourse analyses (e.g., Graham & Witschge, 2003; Price & Capella, 2002). Furthermore, participants’ perceptions of the quality of online discussions are investigated with qualitative interviews (e.g., Engelke, 2019; Ziegele, 2016) or a combina­tion of qualitative interviews and content analy­sis (Díaz Noci et al., 2012). Cross-references Inclusivity is one of five dimensions of deliberative quality in this database written by the same author. Accordingly, there are overlaps with the entries on rationality, interactivity, explicit civility, and storytelling regarding the theoretical background, references/combinations with other methods, and some example studies. Information on Stromer-Galley (2007) Author: Jennifer Stromer-Galley Research question: The aim of the paper was developing a coding scheme for academics and practitioners of deliberation to systematically measure what happens during group deliberations (p. 1; p. 7). Object of analysis: The author conducted a secondary analysis of online group discussions (23 groups with 5-12 participants) in an experiment called “The Virtual Agora Project” at Carnegie Mellon Unversitiy in Pittsburgh, Pennsylvania. Participants attended the discussions from dormitory rooms that were equipped with a computer, headphones, and microphone. The group discussions were recorded and transcribed for analysis (pp. 7-8). Although strictly speaking the study does not analyze media content, the coding scheme has provided the basis for numerous other studies on the deliberative quality of online discussions (e.g., Rowe, 2015; Stroud et al., 2015; Ziegele et al., 2020). Time frame of analysis: Three weeks in July 2004 (p. 7). Info about variables Level of analysis: Equality was measured on the level of the group discussion as well as on the level of the thought. Coders segmented each speaking contribution into thought units as first stage of the coding process. “A thought is defined as an utterance (from a single sentence to multiple sentences) that expresses an idea on a topic. A change in topic signaled a change in thought. A second indicator of a change in thought was a change in the type of talk. The distinct types of talk that this coding captured were the following: talk about the problem of public schools, talk about the process of the talk, talk about the process of the deliberation, and social talk” (p. 9). Variables and values: For measuring the variable equality, the number of speakers within a group was counted. Furthermore, the thoughts were counted for the number of words per thought. Additionally, the total number of thoughts spoken in a given group was counted (p. 15). Reliability: “Two coders spent nearly two months developing and training with the coding scheme. The intercoder agreement measures […] were established from coding 3 of the 23 groups, which were randomly selected. […] The coders of the unitizing process achieved a statistically significant correlation of .86 (p < .001)” (p. 14). Codebook: in the appendix (pp. 22-33) Information on Zimmermann (2017) Author: Tobias Zimmermann Research question: Which role do online reader comments play for a deliberative-democratic understanding of a digital public sphere? (p. 11) Object of analysis: To compare discursive participation online and offline, the author conducted a full-sample content analysis of online reader comments (N = 1.176) and letters to the editor (N = 381) from German local newspapers on three similar conflicts in local politics concerning the renaming of streets and squares. Because the coding scheme was based on the discourse quality index (DQI), only contributions that contained a demand were included in the analysis, that is, “a proposal on what decision should or should not be made” Steenbergen et al., 2003, p. 27). Only then, a speech act is considered relevant from a discourse ethics perspective. Time frame of analysis: June 2012 to May 2013 Info about variables Level of analysis: see Table 1 Variables: Following Stromer-Galley (2007) and Bächtiger et al. (2010), the author operationalizes participation (egalitarian openness) based on frequency and volume of the comments. Furthermore, the study assigns the comments to a pro or contra side in regard to their content. This allows conclusions regarding the equality of different positions (pp. 161-163). Additionally, based on the DQI (Steenbergen et al., 2003), he included the variable common good reference, because reasoning oriented to common interests represents the most inclusive form of reasoning (pp. 190-191). Reliability: Intracoder reliability was tested on a subset of 100 comments. The variable “common good reference” reached a Krippendorff’s Alpha of .71 (p. 201). Codebook: pp. 159-185 (in German) Table 1: Variables, values and level of analysis (Zimmermann, 2017, p. 163; p. 191) Indicator Category Definition Level of analysis Egalitarian openness Egalitarian openness (a) Length of a comment (or letter to the editor) Individual contribution Egalitarian openness (b) Number of contributions per participant Discussion Egalitarian openness (c) Number of contributions per thematic position Discussion Common good reference No common good reference No reference to the common good is explicitly made Individual contribution Explicit common good reference The contribution includes at least one explicit reference to the common good (utilitarian or disadvantaged-oriented) Individual contribution Example studies Ruiz, C., Domingo, D., Micó, J. L., Díaz-Noci, J., Meso, C. & Masip, P. (2011). Public Sphere 2.0? The Democratic Qualities of Citizen Debates in Online Newspapers. The International Journal of Press/Politics, 16, 463–487. Stromer Galley, J. (2007). Measuring Deliberation's Content: A Coding Scheme. Journal of Public Deliberation, 3(1), Article 12. Ziegele, M., Quiring, O., Esau, K. & Friess, D. (2020). Linking News Value Theory With Online Deliberation: How News Factors and Illustration Factors in News Articles Affect the Deliberative Quality of User Discussions in SNS’ Comment Sections. Communication Research, 47(6), 860-890. https://doi.org/10.1177/0093650218797884 Zimmermann, T. (2017). Digitale Diskussionen: Über politische Partizipation mittels Online-Leserkommentaren [Digital discussions: On political participation trough online reader comments]. Edition Politik: Bd. 44. transcript Verlag. http://www.content-select.com/index.php?id=bib_view&ean=9783839438886 Further references Bächtiger, A., Shikano, S., Pedrini, S. & Ryser, M. (2010). Measuring Deliberation 2.0: Standards, Discourse Types, and Sequentialization. University of Konstanz and University of Bern. https://ash.harvard.edu/files/ash/files/baechtiger_0.pdf Díaz Noci, J., Domingo, D., Masip, P., Micó, J. L. & Ruiz, C. (2012). Comments in news, democracy booster or journalistic night­mare: Assessing the quality and dynamics of citizen debates in Catalan online new­spapers. #ISOJ, 2(1), 46–64. https://isoj.org/ wp-content/uploads/2016/10/ISOJ_Jour­nal_V2_N1_2012_Spring.pdf#page=46 Dryzek, J. S., Bächtiger, A., Chambers, S., Cohen, J., Druckman, J. N., Felicetti, A., Fishkin, J. S., Farrell, D. M., Fung, A., Gutmann, A., Landemore, H., Mansbridge, J., Marien, S., Neblo, M. A., Niemeyer, S., Setälä, M., Slothuus, R., Suiter, J., Thompson, D. & Warren, M. E. (2019). The crisis of democracy and the science of deliberation. Science (New York, N.Y.), 363(6432), 1144–1146. https://doi.org/10.1126/science.aaw2694 Engelke, K. M. (2019). Enriching the Conversation: Audience Perspectives on the Deliberative Nature and Potential of User Comments for News Media. Digital Journalism, 8(4), 1–20. https://doi.org/10.1080/21670811.2019.1680567 Esau, K., Friess, D. & Eilders, C. (2017). Design Matters! An Empirical Analysis of Online Deliberation on Different News Platforms. Policy & Internet, 9(3), 321–342. https://doi.org/10.1002/poi3.154 Fishkin, J. S. (1991). Democracy and deliberation: New directions for democratic reform. Yale University Press. http://www.jstor.org/stable/10.2307/j.ctt1dt006v https://doi.org/10.2307/j.ctt1dt006v Friess, D. & Eilders, C. (2015). A systematic review of online deliberation research. Policy & Internet, 7(3), 319–339. https://doi.org/10.1002/poi3.95 Friess, D., Ziegele, M. & Heinbach, D. (2021). Collective Civic Moderation for Deliberation? Exploring the Links between Citizens’ Organized Engagement in Comment Sections and the Deliberative Quality of Online Discussions. Political Communication, 38(5), 624–646. https://doi.org/10.1080/10584609.2020.1830322 Graham, T. & Witschge, T. (2003). In Search of Online Deliberation: Towards a New Method for Examining the Quality of Online Discussions. Communications, 28(2). https://doi.org/10.1515/comm.2003.012 Habermas, J. (2006). Political communication in media society: Does democracy still enjoy an epistemic dimension? The impact of normative theory on empirical research. Communication Theory, 16(4), 411–426. Habermas, J. (2015). Between facts and norms: Contributions to a discourse theory of law and democracy (Reprinted.). Polity Press. Kersting, N. (2008). Innovative Partizipation: Legitimation, Machtkontrolle und Transformation. Eine Einführung [Innovative participation. Legitimation, control of power, and transformation. An introduction]. In N. Kersting (Hrsg.), Politische Beteiligung: Einführung in dialogorientierte Instrumente politischer und gesellschaftlicher Partizipation (S. 11–39). VS Verlag für Sozialwissenschaften. Manin, B. (1987). On Legitimacy and Political Deliberation. Political Theory, 15(3), 338–368. https://doi.org/10.1177/0090591787015003005 Price, V. & Cappella, J. N. (2002). Online deliberation and its influence: The Electronic Dialogue Project in Campaign 2000. IT&Society, 1(1), 303–329. https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.9.5945&rep=rep1&type=pdf Rowe, I. (2015). Deliberation 2.0: Comparing the Deliberative Quality of Online News User Comments Across Platforms. Journal of Broadcasting & Electronic Media, 59(4), 539–555. https://doi.org/10.1080/08838151.2015.1093482 Steenbergen, M. R., Bächtiger, A., Spörndli, M. & Steiner, J. (2003). Measuring Political Deliberation: A Discourse Quality Index. Comparative European Politics, 1(1), 21–48. https://doi.org/10.1057/palgrave.cep.6110002 Stroud, N. J., Scacco, J. M., Muddiman, A., & Curry, A. L. (2015). Changing Deliberative Norms on News Organizations' Facebook Sites. Journal of Computer-Mediated Communication, 20(2), 188–203. https://doi.org/10.1111/jcc4.12104 Ziegele, M. (2016). Nutzerkommentare als Anschlusskommunikation: Theorie und qualitative Analyse des Diskussionswerts von Online-Nachrichten [The Discussion Value of Online News. An Analysis of User Comments on News Platforms]. Springer VS.

Rationality is considered the most important dimension to assess the deliberative quality of online discussions. In quantitative content analyses, it is usually measured with a set of variables, including (among others) reasoning, justification, fact claims, evidence, additional knowledge, and topic relevance. Field of application/Theoretical foundation Most studies on online discussions draw on deliberative theories to measure the quality of their discourse (e.g., Esau et al., 2017; Friess et al., 2021; Rowe, 2015; Ziegele et al., 2020; Zimmermann, 2017). Deliberation is an important concept for the study of (political) online discussions (Ziegele et al., 2020). It focuses on a free and equal exchange of arguments to bridge social differences and legitimize political decisions (Dryzek et al., 2019; Fishkin, 1991, Habermas, 2015). Rationality is considered the most important dimension of deliberative quality, which is inherent in most conceptualizations (Frieß & Eilders, 2015). Rationality is primarily about reasoning, justifications, and facts (Engelke, 2019). Discussion participants should provide justifications and evidence to support their positions (Friess et al., 2021). These reasons and arguments must be both criticizable and verifiable or falsifiable (Esterling, 2011; Habermas, 1995). Counterarguments and different perspectives should also be included (Engelke, 2019; Ziegele et al., 2020). This allows the elaboration of the best arguments in the deliberation process and an informed opinion formation based on these arguments (“the unforced force of the better argument”, Habermas, 2015). A rational discourse and a constructive discussion atmosphere are also considered necessary for reaching a rationally motivated consensus, a central aim of formal deliberation (Cohen, 1989; Friess & Eilders, 2015; Stromer-Galley, 2007). References/Combination with other methods Besides quantitative content analyses, the (deliberative) quality of online discussions is examined with qualitative content analyses and discourse analyses (e.g., Graham & Witschge, 2003; Price & Capella, 2002). Furthermore, participants’ perceptions of the quality of online discussions are investigated with qualitative interviews (e.g., Engelke, 2019; Ziegele, 2016) or a combination of qualitative interviews and content analysis (Díaz Noci et al., 2012). Cross-references Rationality is one of five dimensions of deliberative quality in this database written by the same author. Accordingly, there are overlaps with the entries on interactivity, inclusivity, explicit civility, and storytelling regarding theoretical background, references/combinations with other methods, and some example studies. Information on Heinbach & Wilms (2022) Authors: Dominique Heinbach & Lena K. Wilms (Codebook by Dominique Heinbach, Marc Ziegele, & Lena K. Wilms) Research question: Which attributes differentiate moderated from unmoderated comments? Object of analysis: The quantitative content analysis was based on a stratified random sample of moderated and unmoderated comments (N = 1.682) from the German online participation platform “#meinfernsehen202” [#myTV2021], a citizen participation platform to discuss the future of public broadcasting in Germany. Time frame of analysis: November 24, 2020 to March 3, 2021 Info about variables Level of analysis: User comment Variables and reliability: see Table 1 Table 1: Variables and reliability (Heinbach & Wilms, 2022) Dimension Measure Definition Krippendorff’s α (ordinal) Rationality Topic relevance Does the comment refer to the topic of the post? .70 Fact claims Does the comment contain at least one objectively falsifiable statement with a claim to truth? .78 Reasoning Does the comment contain at least one justification to support a statement (e.g., an assertion, opinion, or claim)? .73 Solution proposal Does the comment contain at least one suggestion on how to resolve problems or issues? .75 Additional knowledge Does the comment contain additional information that is of a knowledge nature of and adds content-related value? .72 Genuine questions Does the comment contain at least one question with a genuine need for information, e.g. questions of knowledge, understanding, justification or opinion? .75 n = 159, 3 coders Values: All variables were coded on a four-point scale (1 = clearly not present; 2 = rather not present; 3 = rather present; 4 = clearly present). Detailed explanations and examples for each value are provided in the Codebook (in German). Codebook: in the appendix of this entry (in German) Information on Zimmermann (2017) Author: Tobias Zimmermann Research question: Which role do online reader comments play for a deliberative-democratic understanding of a digital public sphere? (p. 11) Object of analysis: To compare discursive participation online and offline, the author conducted a full-sample content analysis of online reader comments (N = 1.176) and letters to the editor (N = 381) from German local newspapers on three similar conflicts in local politics concerning the renaming of streets and squares. Because the coding scheme was based on the discourse quality index (DQI), only contributions that contained a demand were included in the analysis, that is, “a proposal on what decision should or should not be made” Steenbergen et al., 2003, p. 27). Only then, a speech act is considered relevant from a discourse ethics perspective. Time frame of analysis: June 2012 to May 2013 Info about variables Variables: Based on the DQI (Steenbergen et al., 2003) the author operationalizes the level of justification as an indicator for rationality. This variable distinguishes four levels of justification (p. 164). Besides the ordinal variable “Level of justification”, the author also uses a dichotomous measurement to distinguish between substantiated and unsubstantiated claims. Level of analysis: Individual contribution Values: see Table 2 Table 2: Variables and Values (pp. 163-166; p. 188) Variable Value Definition Level of Justification No justification The author makes a demand without justifying it argumentatively. The demand stands for itself. Indirect justification The author introduces an argument but its connection to the demand is incomplete, or its justification is not falsifiable. Qualified justification An argument substantiates a demand. A (falsifiable) link is made as to why one should expect that X contributes to or detracts from Y. Detailed justification At least two complete justifications are given, either two complete justifications for the same demand or complete justifications for two different demands (broad justification). Or one justification explains the represented position in depth from several points of view (deep justification). Justification No justification A user makes a demand that X should (not) be done or happen without giving a justification. Justification A user substantiates a demand why X should (not) be done or happen. Reliability: Intracoder reliability was tested on a subset of 100 comments. The ordinal variable “level of justification” exceeded a Krippendorff’s Alpha above .73. The dichotomous variable “justification” reached a Krippendorff’s Alpha of .75 (p. 200-201). Codebook: pp. 159-185 (in German) Information on Ziegele et al. (2020) Authors: Marc Ziegele, Oliver Quiring, Katharina Esau, & Dennis Friess Research questions: RQ1: “Which news factors predict the civility and rationality of reactive user comments?” (p. 869) RQ3: “Which illustration factors predict civil and rational reactive user comments?” (p. 871) Object of analysis: The quantitative content analysis was based on a sample of top-level comments (i.e., comments responding to the article) from the Facebook pages of nine established German news media outlets (N = 11.218). Three artificial weeks were constructed for the sampling of news articles and user comments. On each access day, three or four news articles and the corresponding user comments were randomly selected from each news page. Then, for each article, the oldest five top-level comments, the most recent five top-level comments, five random top-level comments from the middle of the discussion, and the five most popular comments were selected (20 comments per article) (pp. 872-873). Time frame of analysis: May 2015 to August 2015 Info about variables Level of analysis: User comment Variables and reliability: see Table 3 Table 3: Variables and reliability (p. 874) Dimension Measure Definition Krippendorff’s α Rationality Topic relevance Is the comment on-topic? .67 Balance Does the comment include a balanced view on the commented issue? .74 Additional knowledge Does the comment contain additional knowledge? .79 Elaboration Does the comment appear elaborate to the coders? .81 Arguments Does the comment provide reasons for its claims? .74 Analytical Does the comment analyze the background of the issue at hand? .70 Factual claims Does the comment provide facts and factual claims? .72 Questions Does the comment include genuine questions? .80 n = 100, 9 coders Values: “Each factor was coded on 3-point scales (0 = absent, 1 = sporadically present, 2 = highly present)” (p. 874). Example studies Esau, K., Fleuß, D. & Nienhaus, S.‑M. (2021). Different Arenas, Different Deliberative Quality? Using a Systemic Framework to Evaluate Online Deliberation on Immigration Policy in Germany. Policy & Internet, 13(1), 86–112. https://doi.org/10.1002/poi3.232 Esau, K., Friess, D. & Eilders, C. (2017). Design Matters! An Empirical Analysis of Online Deliberation on Different News Platforms. Policy & Internet, 9(3), 321–342. https://doi.org/10.1002/poi3.154 Friess, D., Ziegele, M. & Heinbach, D. (2021). Collective Civic Moderation for Deliberation? Exploring the Links between Citizens’ Organized Engagement in Comment Sections and the Deliberative Quality of Online Discussions. Political Communication, 38(5), 624–646. https://doi.org/10.1080/10584609.2020.1830322 Heinbach, D. & Wilms, L. K. (2022): Der Einsatz von Moderation bei #meinfernsehen2021 [The deployment of moderation at #meinfernsehen2021]. In: F. Gerlach, C. Eilders & K. Schmitz (Eds.): #meinfernsehen2021. Partizipationsverfahren zur Zukunft des öffentlich-rechtlichen Fernsehens. Baden-Baden: Nomos. Monnoyer-Smith, L. & Wojcik, S. (2012). Technology and the quality of public deliberation: a comparison between on and offline participation. International Journal of Electronic Governance, 5(1), Artikel 47443, 24. https://doi.org/10.1504/IJEG.2012.047443 Rowe, I. (2015). Deliberation 2.0: Comparing the Deliberative Quality of Online News User Comments Across Platforms. Journal of Broadcasting & Electronic Media, 59(4), 539–555. https://doi.org/10.1080/08838151.2015.1093482 Stromer Galley, J. (2007). Measuring Deliberation's Content: A Coding Scheme. Journal of Public Deliberation, 3(1), Article 12. Stroud, N. J., Scacco, J. M., Muddiman, A. & Curry, A. L. (2015). Changing Deliberative Norms on News Organizations' Facebook Sites. Journal of Computer-Mediated Communication, 20(2), 188–203. https://doi.org/10.1111/jcc4.12104 Ziegele, M., Quiring, O., Esau, K. & Friess, D. (2020). Linking News Value Theory With Online Deliberation: How News Factors and Illustration Factors in News Articles Affect the Deliberative Quality of User Discussions in SNS’ Comment Sections. Communication Research, 47(6), 860-890. https://doi.org/10.1177/0093650218797884 Zimmermann, T. (2017). Digitale Diskussionen: Über politische Partizipation mittels Online-Leserkommentaren. Edition Politik: Bd. 44. transcript Verlag. http://www.content-select.com/index.php?id=bib_view&ean=9783839438886 Further references Cohen, J. (1989). Deliberation and democratic legitimacy. In A. P. Hamlin & P. Pettit (Hrsg.), The good polity: Normative analysis of the state (S. 67–92). Blackwell. Díaz Noci, J., Domingo, D., Masip, P., Micó, J. L. & Ruiz, C. (2012). Comments in news, democracy booster or journalistic nightmare: Assessing the quality and dynamics of citizen debates in Catalan online newspapers. #ISOJ, 2(1), 46–64. https://isoj.org/wp-content/uploads/2016/10/ISOJ_Journal_V2_N1_2012_Spring.pdf#page=46 Dryzek, J. S., Bächtiger, A., Chambers, S., Cohen, J., Druckman, J. N., Felicetti, A., Fishkin, J. S., Farrell, D. M., Fung, A., Gutmann, A., Landemore, H., Mansbridge, J., Marien, S., Neblo, M. A., Niemeyer, S., Setälä, M., Slothuus, R., Suiter, J., Thompson, D. & Warren, M. E. (2019). The crisis of democracy and the science of deliberation. Science (New York, N.Y.), 363(6432), 1144–1146. https://doi.org/10.1126/science.aaw2694 Engelke, K. M. (2019). Enriching the Conversation: Audience Perspectives on the Deliberative Nature and Potential of User Comments for News Media. Digital Journalism, 8(4), 1–20. https://doi.org/10.1080/21670811.2019.1680567 Esterling, K. M. (2011). “Deliberative Disagreement” in U.S. Health Policy Committee Hearings. Legislative Studies Quarterly, 36(2), 169–198. https://doi.org/10.1111/j.1939-9162.2011.00010.x Fishkin, J. S. (1991). Democracy and deliberation: New directions for democratic reform. Yale University Press. http://www.jstor.org/stable/10.2307/j.ctt1dt006v https://doi.org/10.2307/j.ctt1dt006v Friess, D. & Eilders, C. (2015). A systematic review of online deliberation research. Policy & Internet, 7(3), 319–339. https://doi.org/10.1002/poi3.95 Graham, T. & Witschge, T. (2003). In Search of Online Deliberation: Towards a New Method for Examining the Quality of Online Discussions. Communications, 28(2). https://doi.org/10.1515/comm.2003.012 Habermas, J. (2015). Between facts and norms: Contributions to a discourse theory of law and democracy (Reprinted.). Polity Press. Price, V. & Cappella, J. N. (2002). Online deliberation and its influence: The Electronic Dialogue Project in Campaign 2000. IT&Society, 1(1), 303–329. https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.9.5945&rep=rep1&type=pdf Steenbergen, M. R., Bächtiger, A., Spörndli, M. & Steiner, J. (2003). Measuring Political Deliberation: A Discourse Quality Index. Comparative European Politics, 1(1), 21–48. https://doi.org/10.1057/palgrave.cep.6110002 Ziegele, M. (2016). Nutzerkommentare als Anschlusskommunikation: Theorie und qualitative Analyse des Diskussionswerts von Online-Nachrichten [The Discussion Value of Online News. An Analysis of User Comments on News Platforms]. Springer VS.

The recent threats to a presumed international order posed by acts of heightened terrorism have overshadowed the promise of an emergent order evoked by such concepts as ‘the third way’ and ‘the knowledge society’. Part of the problem with these notions is that they have resonance for only a fairly selective group of intellectuals. Additionally, the terms are somewhat amorphous, so they have not achieved secure purchase in the popular media. But their meanings are not necessarily cancelled by the disordering events of political extremism, worrying as those events are. In the domestic policies of governments, and in workplaces, these other calls to (a beneficent) order continue to be heard and acted upon. The questions are those one must ask of any putative order: what kind of order is it, and is it really beneficial? It is perhaps all the more important to ask these questions when we might be otherwise distracted by the more dramatic events. The End of History? Both the knowledge society and the third way are variations on the ‘end of history’ thesis proposed by the US political scientist, Francis Fukuyama, after the collapse of the Soviet Union. For Fukuyama, as is by now well known, this collapse (for him of Marxism or communism, not just of the Soviet Union) ushered in the triumph of liberalism and capitalism as practiced in the United States and other Western-style democracies. In the third way thesis, as propounded by Anthony Giddens and others, a similar conviction about the bankruptcy of Marxism is accompanied by a more tempered view of liberal capitalism. The third way is, in practice, a middle path between the two, one which recognizes the need for State intervention, not only to condition and discipline the market – which left to its own devices will inevitably have detrimental social effects – but also to facilitate optimum participation in society generally. Hence, the focus of governments on what they call ‘capacity building’, which strongly emphasizes education and training amongst their responsibilities. As a result, the antithesis between communism and capitalism can now appear to have been resolved in a higher synthesis, leaving no room for further dramatic shifts in social organization. The knowledge society – formerly and still sometimes referred to as ‘the knowledge economy’ – has a similar ‘end of history’ flavor because it promises to resolve or at least ameliorate class conflict. It is based on the idea that, increasingly, machines can perform repetitive work, and that basic necessities can be easily met in modern economies. This creates ample scope for product differentiation (niche marketing) and for the provision of cultural goods – entertainment and so on. Everybody will have the opportunity to learn and apply knowledge, and therefore find fulfilling work. Everybody will have the capacity to innovate, and therefore improve the company’s performance, by which each person gains satisfaction and a stake in the future of the business. Technology is also frequently evoked: the interactive new media are said to be particularly amenable to knowledge sharing and innovation. At least in theory, the knowledge society can itself be seen as a third way, or meeting point, between economics and culture, science and arts; and therefore all disciplines, all areas of education and training, are equally important to future social and economic wellbeing. Both these notions have their clear attractions, and can be logically argued to institute improvements on previous orders. But how fully can they achieve their promises, or more importantly, are their promised benefits not just logical entailments but reasonably certain consequences of their social realization? Or can this new order be exploited to the same ends as previous orders? In this short essay, I can do no more than signal a few warnings or reservations concerning the promises that have been made. Social Unity? First of all, both concepts appeal to a putative unity of society, typically grounded in such notions as ‘social capital’ or ‘civil society’. This is problematic, if it is suspected that such unity is a chimera, impossible to achieve, and indeed a dangerous ambition in that it licenses the powerful to find a scapegoat for its elusiveness. Glyn Daly sums the situation up as follows: In every attempt to command the social terrain – to create an antagonism-free new order – various culprits are identified and made responsible for the original loss, or theft, of the fantastical object: Society, Harmony, Salvation, etc. Indeed, the very construction(s) of the social might be understood as a never-ending attempt to solve the original ‘crime’: to identify who has possession of the lost/stolen objects that would enable the full realization/representation of ‘us’. (79) So today, in my own country, New Zealand, we are given a false picture of a nation that lacks enterprise, drives away its best young intellects, can’t convert ideas into business reality, and so on. That paradise of the past when we ‘punched above our weight’, produced Nobel Prize winners and dominated the world in sports, has been stolen away from us. But all around is evidence that is at least partially to the contrary (it is also a fact that it is a big world, and the rest of it is catching up to our once privileged position). Any edition of the Dominion Post’s technology supplement, Info Tech Weekly, is bursting with technological and new media success stories: new start-ups, joint ventures, profitable sellouts, investment from overseas, revolutionary software, value-added agricultural products. Some of these crash and burn: contrary to the myth about the over-gentle, risk-averse New Zealanders, this is sometimes the result of brashness, rashness, and arrogance. New Artisans? Secondly, similar promises about new and improved orders of capitalism have been made before, but the situation was turned to the advantage of capital. In his book on Walter Benjamin, Julian Roberts refers to the ‘cooperative patterns of control’ implied by technology in the new order emerging between the wars. The production management systems that came to be known as Taylorism and Fordism, for example, by instituting processes based on the division of labor, ensured – in theory – that all participants in production were mutually dependent and therefore in some sense equal. Roberts suggests that these new arrangements threatened the old dispensation centered on private ownership of the means of production, and corrective action was not long following. ‘In order to retain this ownership, capitalism . . . resorted to a number of stratagems of which the most important was the division of the world into thinkers and doers, directors and directed, controllers and controlled’ (170). Does contemporary technology, particularly the advent of computers and the Internet as a significant means of production, imply a change in the pattern of control? Conceivably, computer technology and virtual knowledge products (software, etc.) could facilitate a return to a widespread artisan-like mode of production, and we see this to some extent in the new start-ups based on one or a few individuals, engaged in small-scale production. But we have also already seen that where these new enterprises are successful, they tend to expand and subsume, or are bought out by larger concerns. Significantly, we are in a business climate that remains strongly pro-growth, a feature of which is the repeated exhortation of self-employed or small firms to expand, to gear up to an export level of production. In the dissemination of this entrepreneurial message, the business media, which have themselves multiplied in recent years, have played a prominent role. Diverse and Mutually Enriching Knowledges? The concept of knowledge society has come to privilege science and technology. In the news media, as influenced by powerful interests, knowledge society and science and technology are more or less conflated. They are as well in the minds of important people, including those in the all-important research-funding bodies. A pertinent example in New Zealand is the Foundation for Research, Science and Technology. While official foundation publicity is relatively embracing of different approaches to knowledge – ‘the concept of a knowledge society includes the creation, distribution and application of new knowledge to all aspects and across all parts of society’ (FRST, “Foundation’s Role” 4) – specific individual pronouncements betray the actual emphases. For example, in announcing the appointment of a new CEO, the foundation’s Chairman, Neil Richardson said: ‘We live in exciting times and one can sense that the country is finally embracing the value of science and innovation and with it, the concept of a knowledge economy’ (FRST, “Permanent CEO” 1). By such means, ‘knowledge society’ is being used to maintain a division between science and arts, science and culture, when the term’s initial appearance promised a new or renewed awareness of the entanglement of these categories. (This is an outcome which has been only partly mitigated by the burgeoning of the creative industries, since there has been a trend to coining other terms such as ‘the creative economy’ to characterize this phenomenon.) In consequence, a fully nuanced evaluation of the role of scientific and technological development in contemporary society, as well as of its creeping commercialization, is further postponed. Conclusion Immanuel Wallerstein suggests that what he calls the Capitalist World-System has entered a period of transition towards a new system that may or may not be better than the present one. It is possible to imagine that the ‘third way’ and the ‘knowledge society’ – despite the reservations I have outlined – represent a moderating of the capitalist order that will usher in or help condition the arrival of the new. Or failing that, the privileging of knowledge will foster a reflectivity that will enable society to find a better way. Interestingly, however, Wallerstein suspects that such moderation will only prolong the current order, and that something more drastic (if not revolutionary) will be required in the long run if any significant improvement is to be achieved. And as far as reflectivity is concerned, the opposite is arguably true: that ‘knowledge’ merely serves rhetorically to conceal an intensification of the drive for profit and the general expansion of the business mentality. Note I am grateful for the comments of the anonymous referees of this article, which have been helpful in bringing it to its final form. References Daly, Glyn. ‘Politics and the Impossible: Beyond Psychoanalysis and Deconstruction’. Theory, Culture & Society 16.4 (1999): 75-98. Fukuyama, Francis. The End of History and the Last Man. London: Hamish Hamilton, 1992. Foundation for Research, Science and Technology, ‘The Foundation’s Role in Creating Value from Knowledge’. http://www.frst.govt.nz/public/thesource/FRSTrole.htm, 2001. Foundation for Research, Science and Technology. ‘Permanent CEO for FRST’. Media statement, 22 August, 2001. Giddens, Anthony. The Third Way: The Renewal of Social Democracy. Cambridge: Polity Press, 1998. Roberts, Julian. Walter Benjamin. London: Macmillan, 1982. Wallerstein, Immanuel. Unthinking Social Science: The Limits of Nineteenth-century Paradigms. Cambridge: Polity Press, 1991. Citation reference for this article MLA Style Wallace, Derek. "Knowledge Society and Third Way: A New Beneficent Order?." M/C Journal 7.6 (2005). echo date('d M. Y'); ?> <http://journal.media-culture.org.au/0501/03-wallace.php>. APA Style Wallace, D. (Jan. 2005) "Knowledge Society and Third Way: A New Beneficent Order?," M/C Journal, 7(6). Retrieved echo date('d M. Y'); ?> from <http://journal.media-culture.org.au/0501/03-wallace.php>.

Although I'm a rich white guy, I'm also a feminist anti-racism activist who fights for the rights of the poor and oppressed. (Carl Kenner)Systemic bias is a scourge to the pillar of neutrality. (Cerejota)Count me in. Let's leave the bias to the mainstream media. (Orcar967)Because this is so important. (CuttingEdge)These are a handful of comments posted by online editors who have banded together in a virtual coalition to combat Western bias on the world’s largest digital encyclopedia, Wikipedia. This collective action by Wikipedians both acknowledges the inherent inequalities of a user-controlled information project like Wikpedia and highlights the potential for progressive change within that same project. These community members are taking the responsibility of social change into their own hands (or more aptly, their own keyboards).In recent years much research has emerged on Wikipedia from varying fields, ranging from computer science, to business and information systems, to the social sciences. While critical at times of Wikipedia’s growth, governance, and influence, most of this work observes with optimism that barriers to improvement are not firmly structural, but rather they are socially constructed, leaving open the possibility of important and lasting change for the better.WikiProject: Countering Systemic Bias (WP:CSB) considers one such collective effort. Close to 350 editors have signed on to the project, which began in 2004 and itself emerged from a similar project named CROSSBOW, or the “Committee Regarding Overcoming Serious Systemic Bias on Wikipedia.” As a WikiProject, the term used for a loose group of editors who collaborate around a particular topic, these editors work within the Wikipedia site and collectively create a social network that is unified around one central aim—representing the un- and underrepresented—and yet they are bound by no particular unified set of interests. The first stage of a multi-method study, this paper looks at a snapshot of WP:CSB’s activity from both content analysis and social network perspectives to discover “who” geographically this coalition of the unrepresented is inserting into the digital annals of Wikipedia.Wikipedia and WikipediansDeveloped in 2001 by Internet entrepreneur Jimmy Wales and academic Larry Sanger, Wikipedia is an online collaborative encyclopedia hosting articles in nearly 250 languages (Cohen). The English-language Wikipedia contains over 3.2 million articles, each of which is created, edited, and updated solely by users (Wikipedia “Welcome”). At the time of this study, Alexa, a website tracking organisation, ranked Wikipedia as the 6th most accessed site on the Internet. Unlike the five sites ahead of it though—Google, Facebook, Yahoo, YouTube (owned by Google), and live.com (owned by Microsoft)—all of which are multibillion-dollar businesses that deal more with information aggregation than information production, Wikipedia is a non-profit that operates on less than $500,000 a year and staffs only a dozen paid employees (Lih). Wikipedia is financed and supported by the WikiMedia Foundation, a charitable umbrella organisation with an annual budget of $4.6 million, mainly funded by donations (Middleton).Wikipedia editors and contributors have the option of creating a user profile and participating via a username, or they may participate anonymously, with only an IP address representing their actions. Despite the option for total anonymity, many Wikipedians have chosen to visibly engage in this online community (Ayers, Matthews, and Yates; Bruns; Lih), and researchers across disciplines are studying the motivations of these new online collectives (Kane, Majchrzak, Johnson, and Chenisern; Oreg and Nov). The motivations of open source software contributors, such as UNIX programmers and programming groups, have been shown to be complex and tied to both extrinsic and intrinsic rewards, including online reputation, self-satisfaction and enjoyment, and obligation to a greater common good (Hertel, Niedner, and Herrmann; Osterloh and Rota). Investigation into why Wikipedians edit has indicated multiple motivations as well, with community engagement, task enjoyment, and information sharing among the most significant (Schroer and Hertel). Additionally, Wikipedians seem to be taking up the cause of generativity (a concern for the ongoing health and openness of the Internet’s infrastructures) that Jonathan Zittrain notably called for in The Future of the Internet and How to Stop It. Governance and ControlAlthough the technical infrastructure of Wikipedia is built to support and perhaps encourage an equal distribution of power on the site, Wikipedia is not a land of “anything goes.” The popular press has covered recent efforts by the site to reduce vandalism through a layer of editorial review (Cohen), a tightening of control cited as a possible reason for the recent dip in the number of active editors (Edwards). A number of regulations are already in place that prevent the open editing of certain articles and pages, such as the site’s disclaimers and pages that have suffered large amounts of vandalism. Editing wars can also cause temporary restrictions to editing, and Ayers, Matthews, and Yates point out that these wars can happen anywhere, even to Burt Reynold’s page.Academic studies have begun to explore the governance and control that has developed in the Wikipedia community, generally highlighting how order is maintained not through particular actors, but through established procedures and norms. Konieczny tested whether Wikipedia’s evolution can be defined by Michels’ Iron Law of Oligopoly, which predicts that the everyday operations of any organisation cannot be run by a mass of members, and ultimately control falls into the hands of the few. Through exploring a particular WikiProject on information validation, he concludes:There are few indicators of an oligarchy having power on Wikipedia, and few trends of a change in this situation. The high level of empowerment of individual Wikipedia editors with regard to policy making, the ease of communication, and the high dedication to ideals of contributors succeed in making Wikipedia an atypical organization, quite resilient to the Iron Law. (189)Butler, Joyce, and Pike support this assertion, though they emphasise that instead of oligarchy, control becomes encapsulated in a wide variety of structures, policies, and procedures that guide involvement with the site. A virtual “bureaucracy” emerges, but one that should not be viewed with the negative connotation often associated with the term.Other work considers control on Wikipedia through the framework of commons governance, where “peer production depends on individual action that is self-selected and decentralized rather than hierarchically assigned. Individuals make their own choices with regard to resources managed as a commons” (Viegas, Wattenberg and McKeon). The need for quality standards and quality control largely dictate this commons governance, though interviewing Wikipedians with various levels of responsibility revealed that policies and procedures are only as good as those who maintain them. Forte, Larco, and Bruckman argue “the Wikipedia community has remained healthy in large part due to the continued presence of ‘old-timers’ who carry a set of social norms and organizational ideals with them into every WikiProject, committee, and local process in which they take part” (71). Thus governance on Wikipedia is a strong representation of a democratic ideal, where actors and policies are closely tied in their evolution. Transparency, Content, and BiasThe issue of transparency has proved to be a double-edged sword for Wikipedia and Wikipedians. The goal of a collective body of knowledge created by all—the “expert” and the “amateur”—can only be upheld if equal access to page creation and development is allotted to everyone, including those who prefer anonymity. And yet this very option for anonymity, or even worse, false identities, has been a sore subject for some in the Wikipedia community as well as a source of concern for some scholars (Santana and Wood). The case of a 24-year old college dropout who represented himself as a multiple Ph.D.-holding theology scholar and edited over 16,000 articles brought these issues into the public spotlight in 2007 (Doran; Elsworth). Wikipedia itself has set up standards for content that include expectations of a neutral point of view, verifiability of information, and the publishing of no original research, but Santana and Wood argue that self-policing of these policies is not adequate:The principle of managerial discretion requires that every actor act from a sense of duty to exercise moral autonomy and choice in responsible ways. When Wikipedia’s editors and administrators remain anonymous, this criterion is simply not met. It is assumed that everyone is behaving responsibly within the Wikipedia system, but there are no monitoring or control mechanisms to make sure that this is so, and there is ample evidence that it is not so. (141) At the theoretical level, some downplay these concerns of transparency and autonomy as logistical issues in lieu of the potential for information systems to support rational discourse and emancipatory forms of communication (Hansen, Berente, and Lyytinen), but others worry that the questionable “realities” created on Wikipedia will become truths once circulated to all areas of the Web (Langlois and Elmer). With the number of articles on the English-language version of Wikipedia reaching well into the millions, the task of mapping and assessing content has become a tremendous endeavour, one mostly taken on by information systems experts. Kittur, Chi, and Suh have used Wikipedia’s existing hierarchical categorisation structure to map change in the site’s content over the past few years. Their work revealed that in early 2008 “Culture and the arts” was the most dominant category of content on Wikipedia, representing nearly 30% of total content. People (15%) and geographical locations (14%) represent the next largest categories, while the natural and physical sciences showed the greatest increase in volume between 2006 and 2008 (+213%D, with “Culture and the arts” close behind at +210%D). This data may indicate that contributing to Wikipedia, and thus spreading knowledge, is growing amongst the academic community while maintaining its importance to the greater popular culture-minded community. Further work by Kittur and Kraut has explored the collaborative process of content creation, finding that too many editors on a particular page can reduce the quality of content, even when a project is well coordinated.Bias in Wikipedia content is a generally acknowledged and somewhat conflicted subject (Giles; Johnson; McHenry). The Wikipedia community has created numerous articles and pages within the site to define and discuss the problem. Citing a survey conducted by the University of Würzburg, Germany, the “Wikipedia:Systemic bias” page describes the average Wikipedian as:MaleTechnically inclinedFormally educatedAn English speakerWhiteAged 15-49From a majority Christian countryFrom a developed nationFrom the Northern HemisphereLikely a white-collar worker or studentBias in content is thought to be perpetuated by this demographic of contributor, and the “founder effect,” a concept from genetics, linking the original contributors to this same demographic has been used to explain the origins of certain biases. Wikipedia’s “About” page discusses the issue as well, in the context of the open platform’s strengths and weaknesses:in practice editing will be performed by a certain demographic (younger rather than older, male rather than female, rich enough to afford a computer rather than poor, etc.) and may, therefore, show some bias. Some topics may not be covered well, while others may be covered in great depth. No educated arguments against this inherent bias have been advanced.Royal and Kapila’s study of Wikipedia content tested some of these assertions, finding identifiable bias in both their purposive and random sampling. They conclude that bias favoring larger countries is positively correlated with the size of the country’s Internet population, and corporations with larger revenues work in much the same way, garnering more coverage on the site. The researchers remind us that Wikipedia is “more a socially produced document than a value-free information source” (Royal & Kapila).WikiProject: Countering Systemic BiasAs a coalition of current Wikipedia editors, the WikiProject: Countering Systemic Bias (WP:CSB) attempts to counter trends in content production and points of view deemed harmful to the democratic ideals of a valueless, open online encyclopedia. WP:CBS’s mission is not one of policing the site, but rather deepening it:Generally, this project concentrates upon remedying omissions (entire topics, or particular sub-topics in extant articles) rather than on either (1) protesting inappropriate inclusions, or (2) trying to remedy issues of how material is presented. Thus, the first question is "What haven't we covered yet?", rather than "how should we change the existing coverage?" (Wikipedia, “Countering”)The project lays out a number of content areas lacking adequate representation, geographically highlighting the dearth in coverage of Africa, Latin America, Asia, and parts of Eastern Europe. WP:CSB also includes a “members” page that editors can sign to show their support, along with space to voice their opinions on the problem of bias on Wikipedia (the quotations at the beginning of this paper are taken from this “members” page). At the time of this study, 329 editors had self-selected and self-identified as members of WP:CSB, and this group constitutes the population sample for the current study. To explore the extent to which WP:CSB addressed these self-identified areas for improvement, each editor’s last 50 edits were coded for their primary geographical country of interest, as well as the conceptual category of the page itself (“P” for person/people, “L” for location, “I” for idea/concept, “T” for object/thing, or “NA” for indeterminate). For example, edits to the Wikipedia page for a single person like Tony Abbott (Australian federal opposition leader) were coded “Australia, P”, while an edit for a group of people like the Manchester United football team would be coded “England, P”. Coding was based on information obtained from the header paragraphs of each article’s Wikipedia page. After coding was completed, corresponding information on each country’s associated continent was added to the dataset, based on the United Nations Statistics Division listing.A total of 15,616 edits were coded for the study. Nearly 32% (n = 4962) of these edits were on articles for persons or people (see Table 1 for complete coding results). From within this sub-sample of edits, a majority of the people (68.67%) represented are associated with North America and Europe (Figure A). If we break these statistics down further, nearly half of WP:CSB’s edits concerning people were associated with the United States (36.11%) and England (10.16%), with India (3.65%) and Australia (3.35%) following at a distance. These figures make sense for the English-language Wikipedia; over 95% of the population in the three Westernised countries speak English, and while India is still often regarded as a developing nation, its colonial British roots and the emergence of a market economy with large, technology-driven cities are logical explanations for its representation here (and some estimates make India the largest English-speaking nation by population on the globe today).Table A Coding Results Total Edits 15616 (I) Ideas 2881 18.45% (L) Location 2240 14.34% NA 333 2.13% (T) Thing 5200 33.30% (P) People 4962 31.78% People by Continent Africa 315 6.35% Asia 827 16.67% Australia 175 3.53% Europe 1411 28.44% NA 110 2.22% North America 1996 40.23% South America 128 2.58% The areas of the globe of main concern to WP:CSB proved to be much less represented by the coalition itself. Asia, far and away the most populous continent with more than 60% of the globe’s people (GeoHive), was represented in only 16.67% of edits. Africa (6.35%) and South America (2.58%) were equally underrepresented compared to both their real-world populations (15% and 9% of the globe’s population respectively) and the aforementioned dominance of the advanced Westernised areas. However, while these percentages may seem low, in aggregate they do meet the quota set on the WP:CSB Project Page calling for one out of every twenty edits to be “a subject that is systematically biased against the pages of your natural interests.” By this standard, the coalition is indeed making headway in adding content that strategically counterbalances the natural biases of Wikipedia’s average editor.Figure ASocial network analysis allows us to visualise multifaceted data in order to identify relationships between actors and content (Vego-Redondo; Watts). Similar to Davis’s well-known sociological study of Southern American socialites in the 1930s (Scott), our Wikipedia coalition can be conceptualised as individual actors united by common interests, and a network of relations can be constructed with software such as UCINET. A mapping algorithm that considers both the relationship between all sets of actors and each actor to the overall collective structure produces an image of our network. This initial network is bimodal, as both our Wikipedia editors and their edits (again, coded for country of interest) are displayed as nodes (Figure B). Edge-lines between nodes represents a relationship, and here that relationship is the act of editing a Wikipedia article. We see from our network that the “U.S.” and “England” hold central positions in the network, with a mass of editors crowding around them. A perimeter of nations is then held in place by their ties to editors through the U.S. and England, with a second layer of editors and poorly represented nations (Gabon, Laos, Uzbekistan, etc.) around the boundaries of the network.Figure BWe are reminded from this visualisation both of the centrality of the two Western powers even among WP:CSB editoss, and of the peripheral nature of most other nations in the world. But we also learn which editors in the project are contributing most to underrepresented areas, and which are less “tied” to the Western core. Here we see “Wizzy” and “Warofdreams” among the second layer of editors who act as a bridge between the core and the periphery; these are editors with interests in both the Western and marginalised nations. Located along the outer edge, “Gallador” and “Gerrit” have no direct ties to the U.S. or England, concentrating all of their edits on less represented areas of the globe. Identifying editors at these key positions in the network will help with future research, informing interview questions that will investigate their interests further, but more significantly, probing motives for participation and action within the coalition.Additionally, we can break the network down further to discover editors who appear to have similar interests in underrepresented areas. Figure C strips down the network to only editors and edits dealing with Africa and South America, the least represented continents. From this we can easily find three types of editors again: those who have singular interests in particular nations (the outermost layer of editors), those who have interests in a particular region (the second layer moving inward), and those who have interests in both of these underrepresented regions (the center layer in the figure). This last group of editors may prove to be the most crucial to understand, as they are carrying the full load of WP:CSB’s mission.Figure CThe End of Geography, or the Reclamation?In The Internet Galaxy, Manuel Castells writes that “the Internet Age has been hailed as the end of geography,” a bold suggestion, but one that has gained traction over the last 15 years as the excitement for the possibilities offered by information communication technologies has often overshadowed structural barriers to participation like the Digital Divide (207). Castells goes on to amend the “end of geography” thesis by showing how global information flows and regional Internet access rates, while creating a new “map” of the world in many ways, is still closely tied to power structures in the analog world. The Internet Age: “redefines distance but does not cancel geography” (207). The work of WikiProject: Countering Systemic Bias emphasises the importance of place and representation in the information environment that continues to be constructed in the online world. This study looked at only a small portion of this coalition’s efforts (~16,000 edits)—a snapshot of their labor frozen in time—which itself is only a minute portion of the information being dispatched through Wikipedia on a daily basis (~125,000 edits). Further analysis of WP:CSB’s work over time, as well as qualitative research into the identities, interests and motivations of this collective, is needed to understand more fully how information bias is understood and challenged in the Internet galaxy. The data here indicates this is a fight worth fighting for at least a growing few.ReferencesAlexa. “Top Sites.” Alexa.com, n.d. 10 Mar. 2010 ‹http://www.alexa.com/topsites>. Ayers, Phoebe, Charles Matthews, and Ben Yates. How Wikipedia Works: And How You Can Be a Part of It. San Francisco, CA: No Starch, 2008.Bruns, Axel. Blogs, Wikipedia, Second Life, and Beyond: From Production to Produsage. New York: Peter Lang, 2008.Butler, Brian, Elisabeth Joyce, and Jacqueline Pike. Don’t Look Now, But We’ve Created a Bureaucracy: The Nature and Roles of Policies and Rules in Wikipedia. Paper presented at 2008 CHI Annual Conference, Florence.Castells, Manuel. The Internet Galaxy: Reflections on the Internet, Business, and Society. Oxford: Oxford UP, 2001.Cohen, Noam. “Wikipedia.” New York Times, n.d. 12 Mar. 2010 ‹http://www.nytimes.com/info/wikipedia/>. Doran, James. “Wikipedia Chief Promises Change after ‘Expert’ Exposed as Fraud.” The Times, 6 Mar. 2007 ‹http://technology.timesonline.co.uk/tol/news/tech_and_web/article1480012.ece>. Edwards, Lin. “Report Claims Wikipedia Losing Editors in Droves.” Physorg.com, 30 Nov 2009. 12 Feb. 2010 ‹http://www.physorg.com/news178787309.html>. Elsworth, Catherine. “Fake Wikipedia Prof Altered 20,000 Entries.” London Telegraph, 6 Mar. 2007 ‹http://www.telegraph.co.uk/news/1544737/Fake-Wikipedia-prof-altered-20000-entries.html>. Forte, Andrea, Vanessa Larco, and Amy Bruckman. “Decentralization in Wikipedia Governance.” Journal of Management Information Systems 26 (2009): 49-72.Giles, Jim. “Internet Encyclopedias Go Head to Head.” Nature 438 (2005): 900-901.Hansen, Sean, Nicholas Berente, and Kalle Lyytinen. “Wikipedia, Critical Social Theory, and the Possibility of Rational Discourse.” The Information Society 25 (2009): 38-59.Hertel, Guido, Sven Niedner, and Stefanie Herrmann. “Motivation of Software Developers in Open Source Projects: An Internet-Based Survey of Contributors to the Linex Kernel.” Research Policy 32 (2003): 1159-1177.Johnson, Bobbie. “Rightwing Website Challenges ‘Liberal Bias’ of Wikipedia.” The Guardian, 1 Mar. 2007. 8 Mar. 2010 ‹http://www.guardian.co.uk/technology/2007/mar/01/wikipedia.news>. Kane, Gerald C., Ann Majchrzak, Jeremaih Johnson, and Lily Chenisern. A Longitudinal Model of Perspective Making and Perspective Taking within Fluid Online Collectives. Paper presented at the 2009 International Conference on Information Systems, Phoenix, AZ, 2009.Kittur, Aniket, Ed H. Chi, and Bongwon Suh. What’s in Wikipedia? Mapping Topics and Conflict Using Socially Annotated Category Structure. Paper presented at the 2009 CHI Annual Conference, Boston, MA.———, and Robert E. Kraut. Harnessing the Wisdom of Crowds in Wikipedia: Quality through Collaboration. Paper presented at the 2008 Association for Computing Machinery’s Computer Supported Cooperative Work Annual Conference, San Diego, CA.Konieczny, Piotr. “Governance, Organization, and Democracy on the Internet: The Iron Law and the Evolution of Wikipedia.” Sociological Forum 24 (2009): 162-191.———. “Wikipedia: Community or Social Movement?” Interface: A Journal for and about Social Movements 1 (2009): 212-232.Langlois, Ganaele, and Greg Elmer. “Wikipedia Leeches? The Promotion of Traffic through a Collaborative Web Format.” New Media & Society 11 (2009): 773-794.Lih, Andrew. The Wikipedia Revolution. New York, NY: Hyperion, 2009.McHenry, Robert. “The Real Bias in Wikipedia: A Response to David Shariatmadari.” OpenDemocracy.com 2006. 8 Mar. 2010 ‹http://www.opendemocracy.net/media-edemocracy/wikipedia_bias_3621.jsp>. Middleton, Chris. “The World of Wikinomics.” Computer Weekly, 20 Jan. 2009: 22-26.Oreg, Shaul, and Oded Nov. “Exploring Motivations for Contributing to Open Source Initiatives: The Roles of Contribution, Context and Personal Values.” Computers in Human Behavior 24 (2008): 2055-2073.Osterloh, Margit and Sandra Rota. “Trust and Community in Open Source Software Production.” Analyse & Kritik 26 (2004): 279-301.Royal, Cindy, and Deepina Kapila. “What’s on Wikipedia, and What’s Not…?: Assessing Completeness of Information.” Social Science Computer Review 27 (2008): 138-148.Santana, Adele, and Donna J. Wood. “Transparency and Social Responsibility Issues for Wikipedia.” Ethics of Information Technology 11 (2009): 133-144.Schroer, Joachim, and Guido Hertel. “Voluntary Engagement in an Open Web-Based Encyclopedia: Wikipedians and Why They Do It.” Media Psychology 12 (2009): 96-120.Scott, John. Social Network Analysis. London: Sage, 1991.Vego-Redondo, Fernando. Complex Social Networks. Cambridge: Cambridge UP, 2007.Viegas, Fernanda B., Martin Wattenberg, and Matthew M. McKeon. “The Hidden Order of Wikipedia.” Online Communities and Social Computing (2007): 445-454.Watts, Duncan. Six Degrees: The Science of a Connected Age. New York, NY: W. W. Norton & Company, 2003Wikipedia. “About.” n.d. 8 Mar. 2010 ‹http://en.wikipedia.org/wiki/Wikipedia:About>. ———. “Welcome to Wikipedia.” n.d. 8 Mar. 2010 ‹http://en.wikipedia.org/wiki/Main_Page>.———. “Wikiproject:Countering Systemic Bias.” n.d. 12 Feb. 2010 ‹http://en.wikipedia.org/wiki/Wikipedia:WikiProject_Countering_systemic_bias#Members>. Zittrain, Jonathan. The Future of the Internet and How to Stop It. New Haven, CT: Yale UP, 2008.