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1
Kumar, Amit, and Sonali Agarwal. "Leveraging multifaceted proximity measures among developers in predicting future collaborations to improve the social capital of software projects." JUCS - Journal of Universal Computer Science 27, no. (11) (2021): 1240–71. https://doi.org/10.3897/jucs.76602.
Full textAbstract:
Social capital is an asset earned by people through their social connections. One of the motivations among developers to contribute to open source development and maintenance tasks is to earn social capital. Recent studies suggest that the social capital of the project has an impact on the sustained participation of the developers in open source software (OSS). One way to improve the social capital of the project is to help the developers in connecting with their peers. However, to the best of our knowledge, there is no prior research which attempts to predict future collaborations among developers and establish the significance of these collaborations on improving the social capital at the project level. To address this research gap, in this paper, we model the past collaborations among developers on version control system (VCS) and issue tracking system (ITS) as homogeneous and heterogeneous developer social network (DSN). Along with the novel path count based features, defined on proposed heterogeneous DSN, multifaceted proximity features are used to generate a feature set for machine learning classifiers. Our experiments performed on 5 popular open source projects (Spark, Kafka, Flink, WildFly, Hibernate) indicate that the proposed approach can predict the future collaborations among developers on both the platforms i.e. VCS as well as ITS with a significant accuracy (AUROC up to 0.85 and 0.9 for VCS and ITS respectively). A generic metric- recall of gain in social capital is proposed to investigate the efficacy of these predicted collaborations in improving the social capital of the project. We also concretised this metric on various measures of social capital and found that collaborations predicted by our approach have significant potential to improve the social capital at project level (e.g. Recall of gain in cohesion index up to 0.98 and Recall of gain in average godfather index up to 0.99 for VCS). We also showed that structure of collaboration network has an impact on the accuracy and usefulness of predicted collaborations. Since the past research suggests that many newcomers abandon the open source project due to social barriers which they face after joining the project, our research outcomes can be used to build the recommendation systems which might help to retain such developers by improving their social ties based on similar skills/interests.
2
Ji, Fujiao, Zhongying Zhao, Hui Zhou, Heng Chi, and Chao Li. "A comparative study on heterogeneous information network embeddings." Journal of Intelligent & Fuzzy Systems 39, no. 3 (2020): 3463–73. http://dx.doi.org/10.3233/jifs-191796.
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Heterogeneous information networks are widely used to represent real world applications in forms of social networks, word co-occurrence networks, and communication networks, etc. However, It is difficult for traditional machine learning methods to analyze these networks effectively. Heterogeneous information network embedding aims to convert the network into low dimensional vectors, which facilitates the following tasks. Thus it is receiving tremendous attention from the research community due to its effectiveness and efficiency. Although numerous methods have been present and applied successfully, there are few works to make a comparative study on heterogeneous information network embedding, which is very important for developers and researchers to select an appropriate method. To address the above problem, we make a comparative study on the heterogeneous information network embeddings. Specifically, we first give the problem definition of heterogeneous information network embedding. Then the heterogeneous information networks are classified into four categories from the perspective of network type. The state-of-the-art methods for each category are also compared and reviewed. Finally, we make a conclusion and suggest some potential future research directions.
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R, Balamurugan, Dhivakar M, Muruganantham G, and Ramprakash S. "Securing Heterogeneous Privacy Protection in Social Network Records based Encryption Scheme." International Journal on Recent and Innovation Trends in Computing and Communication 7, no. 3 (2019): 10–13. http://dx.doi.org/10.17762/ijritcc.v7i3.5249.
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This survey places of interest the major issues concerning privacy and security in online social networks. Firstly, we discuss investigate that aims to protect user data from the an assortment of attack vantage points together with other users, advertisers, third party request developers, and the online social arrangement provider itself. Next we cover social network supposition of user attributes, locate hubs, and link prediction. Because online social networks are so saturated with sensitive information, network inference plays a major privacy role. Social Networking sites go upwards since of all these reasons. In recent years indicates that for many people they are now the mainstream communication knowledge. Social networking sites come under few of the most frequently browsed categories websites in the world. Nevertheless Social Networking sites are also vulnerable to various problems threats and attacks such as revelation of information, identity thefts etc. Privacy practice in social networking sites often appear convoluted as in sequence sharing stands in discord with the need to reduce disclosure-related abuses. Facebook is one such most popular and widely used Social Networking sites which have its own healthy set of Privacy policy.
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Li, Xiang, and Bocheng Hou. "Competing Complex Information Spreading in Multiplex Social Network." Complexity 2021 (May 11, 2021): 1–9. http://dx.doi.org/10.1155/2021/9923837.
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Coevolution spreading dynamics on complex networks is a hot topic, which attracts much attention in network science. This paper proposes a mathematical model to describe the two competing complex information spreading dynamics on multiplex networks. An individual can only accept one of the two pieces of information. A heterogeneous mean-field theory is developed to describe the spreading dynamics. We reveal different regions through Monte Carlo simulations of the competing complex information spreading dynamics: no global information, one information dominant, and two information coexistence. We finally find that the heterogeneity of the multiplex networks’ degree distributions does not qualitatively affect the results.
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Li, Zhen, Zhisong Pan, Yanyan Zhang, Guopeng Li, and Guyu Hu. "Efficient Community Detection in Heterogeneous Social Networks." Mathematical Problems in Engineering 2016 (2016): 1–15. http://dx.doi.org/10.1155/2016/5750645.
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Community detection is of great importance which enables us to understand the network structure and promotes many real-world applications such as recommendation systems. The heterogeneous social networks, which contain multiple social relations and various user generated content, make the community detection problem more complicated. Particularly, social relations and user generated content are regarded as link information and content information, respectively. Since the two types of information indicate a common community structure from different perspectives, it is better to mine them jointly to improve the detection accuracy. Some detection algorithms utilizing both link and content information have been developed. However, most works take the private community structure of a single data source as the common one, and some methods take extra time transforming the content data into link data compared with mining directly. In this paper, we propose a framework based on regularized joint nonnegative matrix factorization (RJNMF) to utilize link and content information jointly to enhance the community detection accuracy. In the framework, we develop joint NMF to analyze link and content information simultaneously and introduce regularization to obtain the common community structure directly. Experimental results on real-world datasets show the effectiveness of our method.
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Letch, Nick. "Ecologies of interests in social information systems for social benefit." Information Technology & People 29, no. 1 (2016): 14–30. http://dx.doi.org/10.1108/itp-09-2014-0218.
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Purpose – The purpose of this paper is to explore a class of social information systems which are purposefully designed to address wider social objectives. Specifically, the paper investigates the embedding of ICTs into the wider networks of social policy action and explores issues associated with the integration of social information systems into complex problem domains. Design/methodology/approach – A case study of a social information system and its integration into networks of actors with an interest in the underlying social concern is presented. The system under analysis is first described in terms of the emerging characteristics used to define this class of social information system. The wider policy network in which the social information system is implemented is then described and the integration of the social information system into the wider network is discussed. Findings – The case study illustrates that for complex social problems, there can be multiple interests embedded in an ecology of sub-networks. Each sub-network can make use of the social information system in different ways which creates difficulties in the social information system gaining sufficient legitimacy to be institutionalised into the wider policy network. Originality/value – The paper extends understanding of social information systems by proposing that a class of social information systems are developed to pursue human benefit. Recognising the context in which these systems are integrated as an ecology of interests, shifts the focus of social information systems design from examining the requirements of a relatively homogenous community of actors to understanding how social information systems can be developed to enable information exchange within and across heterogeneous communities.
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Kumar, Amit, and Sonali Agarwal. "Leveraging multifaceted proximity measures among developers in predicting future collaborations to improve the social capital of software projects." JUCS - Journal of Universal Computer Science 27, no. 11 (2021): 1240–71. http://dx.doi.org/10.3897/jucs.76602.
Full textAbstract:
Social capital is an asset earned by people through their social connections. One of the motivations among developers to contribute to open source development and maintenance tasks is to earn social capital. Recent studies suggest that the social capital of the project has an impact on the sustained participation of the developers in open source software (OSS). One way to improve the social capital of the project is to help the developers in connecting with their peers. However, to the best of our knowledge, there is no prior research which attempts to predict future collaborations among developers and establish the significance of these collaborations on improving the social capital at the project level. To address this research gap, in this paper, we model the past collaborations among developers on version control system (VCS) and issue tracking system (ITS) as homogeneous and heterogeneous developer social network (DSN). Along with the novel path count based features, defined on proposed heterogeneous DSN, multifaceted proximity features are used to generate a feature set for machine learning classifiers. Our experiments performed on 5 popular open source projects (Spark, Kafka, Flink, WildFly, Hibernate) indicate that the proposed approach can predict the future collaborations among developers on both the platforms i.e. VCS as well as ITS with a significant accuracy (AUROC up to 0.85 and 0.9 for VCS and ITS respectively). A generic metric- recall of gain in social capital is proposed to investigate the efficacy of these predicted collaborations in improving the social capital of the project. We also concretised this metric on various measures of social capital and found that collaborations predicted by our approach have significant potential to improve the social capital at project level (e.g. Recall of gain in cohesion index up to 0.98 and Recall of gain in average godfather index up to 0.99 for VCS). We also showed that structure of collaboration network has an impact on the accuracy and usefulness of predicted collaborations. Since the past research suggests that many newcomers abandon the open source project due to social barriers which they face after joining the project, our research outcomes can be used to build the recommendation systems which might help to retain such developers by improving their social ties based on similar skills/interests.
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Yu, Ruiyun, Pengfei Wang, and Shiyang Liao. "LAPM: The Location Aware Prediction Model in Human Sensing Systems." International Journal of Distributed Sensor Networks 2015 (2015): 1–12. http://dx.doi.org/10.1155/2015/814174.
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The mobile human social network actually might be the hugest and best “sensor network” because of the explosive growth in social network content. Nowadays, more and more mobile social applications offer a much easier way for people to share their feeling including vision, haptic, hearing, and smell with the location information by words, images, or even videos. These new sharing methods appearing in the mobile social network actually give us a precious chance to sense the world. Extra systems, which are specialized in particular sensing, do not need to be created any more. The specific sensing data can be acquired from the social network by handling the heterogeneous data. The contribution of this paper lies in developing a model that collects samples considering the relevancy from the perspective of location from different mobile social networks and estimating the occurrence likelihood of the perceived event with collected samples. The simulations and real-world case studies are also developed to verify the reliability of the model and the effectiveness of the Location Aware EM algorithm.
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Hoang Tu, Duong Quoc, Alla Grigorievna Kravets, Thanh Viet Nguyen, and Inna Vladimirovna Strukova. "ANALYSIS OF THE INFLUENCE METRIC OF DEVELOPERS IN THE R LANGUAGE IN THE GITHUB." ITNOU: Information technologies in science, education and management 115 (2021): 14–19. http://dx.doi.org/10.47501/itnou.2021.1.14-19.
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Social Programming Sites (SPSs) are social networking services for sharing software devel-opment projects on the Internet. Many open source projects are currently being developed on the SPSs. One of the characteristics of SPSs is that they provide a social media platform that encourages collaboration between developers with similar interests and goals. The article proposes an approach to the formation of a Github SPSs graph as a heterogeneous network. On the basis of this approach, the metric of determining the developers of the most used R packages is investigated.
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Zhang, Chengyuan, Yang Wang, Lei Zhu, Jiayu Song, and Hongzhi Yin. "Multi-Graph Heterogeneous Interaction Fusion for Social Recommendation." ACM Transactions on Information Systems 40, no. 2 (2022): 1–26. http://dx.doi.org/10.1145/3466641.
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With the rapid development of online social recommendation system, substantial methods have been proposed. Unlike traditional recommendation system, social recommendation performs by integrating social relationship features, where there are two major challenges, i.e., early summarization and data sparsity. Thus far, they have not been solved effectively. In this article, we propose a novel social recommendation approach, namely Multi-Graph Heterogeneous Interaction Fusion (MG-HIF), to solve these two problems. Our basic idea is to fuse heterogeneous interaction features from multi-graphs, i.e., user–item bipartite graph and social relation network, to improve the vertex representation learning. A meta-path cross-fusion model is proposed to fuse multi-hop heterogeneous interaction features via discrete cross-correlations. Based on that, a social relation GAN is developed to explore latent friendships of each user. We further fuse representations from two graphs by a novel multi-graph information fusion strategy with attention mechanism. To the best of our knowledge, this is the first work to combine meta-path with social relation representation. To evaluate the performance of MG-HIF, we compare MG-HIF with seven states of the art over four benchmark datasets. The experimental results show that MG-HIF achieves better performance.
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Zhang, Chong, Zhenkun Zhou, Xingyu Peng, and Ke Xu. "DoubleH: Twitter User Stance Detection via Bipartite Graph Neural Networks." Proceedings of the International AAAI Conference on Web and Social Media 18 (May 28, 2024): 1766–78. http://dx.doi.org/10.1609/icwsm.v18i1.31424.
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Given the development and abundance of social media, studying the stance of social media users is a challenging and pressing issue. Social media users express their stance by posting tweets and retweeting. Therefore, the homogeneous relationship between users and the heterogeneous relationship between users and tweets are relevant for the stance detection task. Recently, graph neural networks (GNNs) have developed rapidly and have been applied to social media research. In this paper, we crawl a large-scale dataset of the 2020 US presidential election and automatically label all users by manually tagged hashtags. Subsequently, we propose a bipartite graph neural network model, DoubleH, which aims to better utilize homogeneous and heterogeneous information in user stance detection tasks. Specifically, we first construct a bipartite graph based on posting and retweeting relations for two kinds of nodes, including users and tweets. We then iteratively update the node's representation by extracting and separately processing heterogeneous and homogeneous information in the node's neighbors. Finally, the representations of user nodes are used for user stance classification. Experimental results show that DoubleH outperforms the state-of-the-art methods on popular benchmarks. Further analysis illustrates the model's utilization of information and demonstrates stability and efficiency at different numbers of layers.
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Li, Ying, Xiao Zhang, Yu Liang, and Qianqian Li. "Automatic Controversy Detection Based on Heterogeneous Signed Attributed Network and Deep Dual-Layer Self-Supervised Community Analysis." Entropy 27, no. 5 (2025): 473. https://doi.org/10.3390/e27050473.
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In this study, we propose a computational approach that applies text mining and deep learning to conduct controversy detection on social media platforms. Unlike previous research, our method integrates multidimensional and heterogeneous information from social media into a heterogeneous signed attributed network, encompassing various users’ attributes, semantic information, and structural heterogeneity. We introduce a deep dual-layer self-supervised algorithm for community detection and analyze controversy within this network. A novel controversy metric is devised by considering three dimensions of controversy: community distinctions, betweenness centrality, and user representations. A comparison between our method and other classical controversy measures such as Random Walk, Biased Random Walk (BRW), BCC, EC, GMCK, MBLB, and community-based methods reveals that our model consistently produces more stable and accurate controversy scores. Additionally, we calculated the level of controversy and computed p-values for the detected communities on our crawled dataset Weibo, including #Microblog (3792), #Comment (45,741), #Retweet (36,126), and #User (61,327). Overall, our model had a comprehensive and nuanced understanding of controversy on social media platforms. To facilitate its use, we have developed a user-friendly web server.
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Ernst, Christoph, Andreas Mladenow, and Christine Strauss. "Collaboration and crowdsourcing in emergency management." International Journal of Pervasive Computing and Communications 13, no. 2 (2017): 176–93. http://dx.doi.org/10.1108/ijpcc-03-2017-0026.
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Purpose Emergency managers face coordinative challenges that require a high degree of mobility, flexibility and the ability to interpret heterogeneous, location-dependent information of various sources and quality. Recent information and communication technology-driven developments like crowdsourcing or social networks have opened up new organizational possibilities for emergency managers. To make quick but solid decisions, and improve the coordination of activities performed by crowdsourcees during disaster response, the authors suggest the use of collaborative features from crowdsourcing and inherent availability of resources from social network effects. In this paper, the idea of considering collaboration and crowdsourcing as drivers for flexibility in the design of business processes in the context of emergency management is prepared, the meaning of location-dependent tasks for volunteers is investigated, and the added value of social network effects is substantiated. Design/methodology/approach This paper is part of an ongoing research project in the field of crowdsourcing. It represents conceptual work that builds on relevant literature. Findings In terms of emergency management, the paper sheds light on what emergency managers may consider when coordinating activities performed by volunteers and how they may benefit from social network effects. Furthermore, it is shown how they can exploit information using collaboration-based and tournament-like crowdsourcing, how they can benefit from invoking additional resources using weak ties from social networks, and how visualization of information may support decision-making. Practical implications Exemplary applications to exploit crowdsourcing and social network effects to support improvisation and to respond flexibly in disaster response are given. Originality/value This paper suggests novel collaborative approaches to support emergency managers in their decision-making. Based on social network analysis, the value of weak ties is elaborated, and based on a taxonomy from crowdsourcing, distinct collaborative alternatives are developed and proposed for application in emergency management.
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Wang, Yan, Feng Qing, and Ming Yan. "Dynamics of 2SIH2R Rumor-Spreading Model in a Heterogeneous Network." Wireless Communications and Mobile Computing 2022 (January 17, 2022): 1–13. http://dx.doi.org/10.1155/2022/7398387.
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Due to the development of social media, the threshold for information dissemination has become lower than ever before. As a special kind of information, rumors are usually harmful and are usually accompanied by a high degree of ambiguity that makes them difficult to immediately identify, but “rumors stop at wise men.” When someone identifies a rumor as false and begins spreading the truth instead, a confrontational relationship obtains between the rumor and the truth that leads to the stifling of the former. Given this, we developed a 2SIH2R model in this study that contains mechanisms of discernment and confrontation in a heterogeneous network to examine the dissemination of the rumor and the truth. By using mean-field equations of the 2SIH2R model, the threshold of the spreading of each can be determined separately in three cases. The results of a numerical simulation show that under the same conditions, the greater is the mechanism of discernment or confrontation, the smaller is the instantaneous maximum influence and the final range of influence of the rumor. It can be also concluded that the earlier release of the truth about the event by the government can significantly control the rumor. Secondly, it is more effective to publish the truth in advance than after the rumor has appeared. Thirdly, it is more important for the government to increase education and improve the ability of citizens to reveal the rumor than to increase the spread of the truth after the rumor occurs. These results can be used to help reduce the harmful effects of rumors.
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Weber, Hannes, Marc Schwenzer, and Steffen Hillmert. "Homophily in the formation and development of learning networks among university students." Network Science 8, no. 4 (2020): 469–91. http://dx.doi.org/10.1017/nws.2020.10.
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AbstractStudents’ personal learning networks can be a valuable resource of success in higher education: they offer opportunities for academic and personal support and provide sources of information related to exams or homework. We study the determinants of learning networks using a panel study among university students in their first and second year of study. A long-standing question in social network analysis has been whether the tendency of individuals with similar characteristics to form ties is a result of preferences “choice homophily” or rather selective opportunities “induced homophily”. We expect a latent preference for homophilic learning partnerships with regard to attributes, such as gender, ability, and social origin. We estimate recently developed temporal exponential random graph models to control for previous network structure and study changes in learning ties among students. The results show that especially for males, same-gender partnerships are preferred over heterogeneous ties, while chances for tie formation decrease with the difference in academic ability among students. Social origin is a significant factor in the crosssectional exploration but does appear to be less important in the formation of new (strong) partnerships during the course of studies.
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Ghinea, Gabriela-Nouella. "Social networks in the cosponsorship legislative behavior: theoretical explorations." Revista Calitatea Vieții 33, no. 1 (2022): 1–15. http://dx.doi.org/10.46841/rcv.2022.01.02.
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Legislation adoption is a complex process which brings together assorted actors, each with its own array of attributes, strategies and motives. Legislators rely on the web created for a diverse array of functions, from information diffusion to coalition building. Given its heterogeneous nature, legislative cosponsorship networks have gradually become a focus point in the study of collaborative activity in political settings. The article looks into the history of how social network analysis has been adopted in the study of cosponsorship patterns, at the most used methodologies, explanatory variables and applications within this subfield. It looks at the multiple studies that are dealing with the variables facilitating voluntary cooperation, how they may vary in performance given different national contexts, and how personal interests and institutional constraints (or incentives) intertwine. The last chapter deals with research developed using lessons learned from studying legislative networks. Keywords: social network analysis; cosponsorship networks; legislative networks; centrality measures; explanatory variables; data gathering. ●●●●● Procesul de adoptare a unei legi este unul complex, care reunește o serie de actori, fiecare cu propria sa gamă de atribute, strategii și motive. Legiuitorii se bazează pe rețeaua din care fac parte pentru o gamă variată de funcții, de la difuzarea informațiilor până la construirea de coaliții. Rețelele de cosponsorizare legislativă au devenit treptat un punct focal în studiul activității de colaborare în medii politice. Acest articol aduce în prim-plan istoria modului în care analiza rețelelor sociale a fost adoptată în studiul modelelor de cosponsorizare, discută cele mai utilizate metodologii, variabile explicative și aplicații din acest subdomeniu. Sunt analizate multiplele studii care se ocupă de variabilele ce facilitează cooperarea voluntară, modul în care acestea pot varia în performanță în funcție de diferite contexte naționale, dar și de modul în care interesele personale și constrângerile instituționale (sau stimulentele) acționează asupra rețeleleor de cosponsorizare legislativă. Ultimul capitol tratează cercetările dezvoltate folosind lecțiile învățate din studierea rețelelor legislative. Cuvinte-cheie: analiza rețelelor sociale; rețele de cosponsorizare; rețele legislative; măsuri de centralitate; variabile explicative; colectare de date.
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Kontro, Inkeri, and Mathieu Génois. "Combining Surveys and Sensors to Explore Student Behaviour." Education Sciences 10, no. 3 (2020): 68. http://dx.doi.org/10.3390/educsci10030068.
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Student belongingness is important for successful study paths, and group work forms an important part of modern university physics education. To study the group dynamics of introductory physics students at the University of Helsinki, we collected network data from seven laboratory course sections of approximately 20 students each for seven consecutive weeks. The data was collected via the SocioPatterns platform, and supplemented with students’ major subject, year of study and gender. We also collected the Mechanics Baseline Test to measure physics knowledge and the Colorado Learning Attitudes about Science Survey to measure attitudes. We developed metrics for studying the small networks of the laboratory sessions by using connections of the teaching assistant as a constant. In the network, we found both demographically homogeneous and heterogeneous groups that are stable. While some students are consistently loosely connected to their networks, we were not able to identify risk factors. Based on our results, the physics laboratory course is equally successful in building strongly connected groups regardless of student demographics in the sections or the formed small groups. SocioPatterns supplemented with surveys thus provides an opportunity to look into the dynamics of students’ social networks.
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Denisova, Galina, Irina Polonskaya, and Elena Susimenko. "Actor-network theory: innovative aspects of sociological methodology." Vestnik instituta sotziologii 13, no. 2 (2022): 137–58. http://dx.doi.org/10.19181/vis.2022.13.2.797.
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In recent years, a discussion about the dissatisfaction of scientists with the current state of sociology has intensified in the world sociological community. In this situation, various ways of raising the scientific level of sociology as a whole are proposed. One of them was proposed by B. Latour in the framework of the actor-network theory (ANT), the theoretical concepts of which were further developed in the works of his like-minded colleages. Representatives of the Russian sociology are actively involved in a versatile study of the contribution made by the ANT to the development of sociology. The article studies the basic provisions of the actor-network theory concerning the subject specifics of sociological knowledge, the fundamental difference between the definition of understanding the subject of ANT sociology and the definitions given by traditional sociological trends and paradigms, as well as the consequences of this innovative understanding for the formation of methodological principles for studying social reality. The authors also dwell on the consideration of the most fundamental and controversial methodological innovation of ANT - the “turn to things” and the introduction of the concept of heterogeneity of agents into the understanding of social processes.
 Particular attention in the article is paid to the analysis of the meaning of the term “actant”, innovative for sociology, borrowed by the ANT from the semiotic theory of narrative and incorporated into sociology and ontology of the network of associations of heterogeneous actants. Concerning the disagreements between the actor-network theory and the sociological mainstream of our time, the authors dwell on the criticism by ANT theorists of the sociological "metaphysics of social forces", understood as a way of theoretical legitimation of social inequality. The purpose of the article is to clarify the unity and interconnection of the key innovative positions of ANT in sociological methodology, and through this, to substantiate the significance and heuristic potential of the innovations proposed by the actor-network theory for raising the scientific level of sociology in the study of social reality. As a result, the authors demonstrate the methodological turn of ANT, that makes possible overcoming the gap between sociological theory and social and political practice, thus opening the way for building a new attitude of sociology to reality, returning it to solving not only scientific, but also social and practical problems.
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Dhurandhar, A., and J. Wang. "Single Network Relational Transductive Learning." Journal of Artificial Intelligence Research 48 (November 30, 2013): 813–39. http://dx.doi.org/10.1613/jair.4068.
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Relational classification on a single connected network has been of particular interest in the machine learning and data mining communities in the last decade or so. This is mainly due to the explosion in popularity of social networking sites such as Facebook, LinkedIn and Google+ amongst others. In statistical relational learning, many techniques have been developed to address this problem, where we have a connected unweighted homogeneous/heterogeneous graph that is partially labeled and the goal is to propagate the labels to the unlabeled nodes. In this paper, we provide a different perspective by enabling the effective use of graph transduction techniques for this problem. We thus exploit the strengths of this class of methods for relational learning problems. We accomplish this by providing a simple procedure for constructing a weight matrix that serves as input to a rich class of graph transduction techniques. Our procedure has multiple desirable properties. For example, the weights it assigns to edges between unlabeled nodes naturally relate to a measure of association commonly used in statistics, namely the Gamma test statistic. We further portray the efficacy of our approach on synthetic as well as real data, by comparing it with state-of-the-art relational learning algorithms, and graph transduction techniques with an adjacency matrix or a real valued weight matrix computed using available attributes as input. In these experiments we see that our approach consistently outperforms other approaches when the graph is sparsely labeled, and remains competitive with the best when the proportion of known labels increases.
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AlSuwaidan, Lulwah, and Nuha Almegren. "Validating the Adoption of Heterogeneous Internet of Things with Blockchain." Future Internet 12, no. 6 (2020): 107. http://dx.doi.org/10.3390/fi12060107.
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Emerging technologies such as Internet of Things (IoT) and blockchain have affected the digital transformation. Blockchain, on the one hand, was initially developed for the purpose of financial trading due to its robustness especially for fault tolerance and cryptographic security in addition to its decentralized architecture. IoT, on the other hand, is an open interconnected network of smart devices able to communicate simultaneously. This arises a challenge in privacy and security, specifically for the data being exchanged. To overcome this, studies have focused on the blockchain to resolve the security and privacy issues of IoT. Indeed, limited studies have proposed to assess blockchain’s viability for IoT and the associated challenges. In this paper, a conceptual model has proposed to identify the crucial factors affecting the adoption of blockchain in IoT. The model consists of four dimensions of factors that we assume will affect the adoption of the two technologies. The dimensions are: attitude-related factors, social influence related factors, data-related factors, and security-related factors. This model is validated through a survey that was distributed between professionals in blockchain and IoT. The findings show a significant impact of data-related factors on the adoption of blockchain in IoT and the intention to use them. The model can play an important role in the development of strategies, standards, and performance assessment.
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Liu, Guiwen, Kehao Chen, Juan Huang, and Xun Deng. "Analysis of the Spatiotemporal Heterogeneity of Housing Prices’ Association in China: An Urban Agglomeration Perspective." Buildings 12, no. 7 (2022): 972. http://dx.doi.org/10.3390/buildings12070972.
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With the rise of urban agglomerations, regional divergence of China’s real estate market has gradually intensified. City-specialized policies have become the main emphasis for promoting the healthy development of the regional real estate market. By adopting a gravity model, social net-work analysis, and impulse response analysis, this paper examines the spatial-temporal heterogeneity of housing prices’ association in the Beijing-Tianjin-Hebei Urban Agglomeration (BTH-UA), the Yangtze River Delta Urban Agglomeration (YRDUA), and the Pearl River Delta Urban Agglomeration (PRDUA), which are the most developed urban agglomerations in China. Meanwhile, the formation mechanism of the housing prices’ association network and spillover effect in urban agglomeration were theoretically analyzed. This paper found that (1) significant aggregation phenomena of housing prices were observed in the urban agglomerations; (2) characteristics of overall and individual networks were dynamically heterogeneous. In the BTHUA and the PRDUA, the associations of housing prices were polarized and sparse, while they were more linked and complex in the YRDUA; (3) polycentric network structure has been demonstrated in the urban agglomerations and the spillover effects of central cities varied in intensity and breadth on responding cities and persisted during the lag period. Accordingly, several policy recommendations have been made.
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Gargouri, Mohamed Amine, Nadia Hamani, Nassim Mrabti, and Lyes Kermad. "Optimization of the Collaborative Hub Location Problem with Metaheuristics." Mathematics 9, no. 21 (2021): 2759. http://dx.doi.org/10.3390/math9212759.
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By creating new job opportunities and developing the regional economy, the transport of goods generates significant costs, environmental and sanitary nuisances, and high greenhouse gas (GHG) emissions. In this context, collaboration is an interesting solution that can be used to enable companies to overcome some problems such as globalization, economic crisis, health crisis, issues related to sustainability, etc. This study deals with the design of a multiperiod multiproduct three-echelon collaborative distribution network with a heterogeneous fleet. By applying the mixed integer linear problem (MILP) formulations, it was possible to study the three dimensions of sustainability (economic, environmental, and social/societal). Since the examined problem was NP-hard, it was solved using four metaheuristic approaches to minimize the different logistics costs or CO2 emissions. The social/societal aspect evaluated the accident rate and the noise level generated by the freight transport. Four algorithms were developed to achieve our objectives: a genetic algorithm, a simulated annealing, a particle swarm algorithm, and a vibration damping optimization algorithm. Considering a French distribution network, these algorithms overcame the limits of the exact solution method by obtaining optimal solutions with reasonable execution time.
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Hou, Shifu, Yujie Fan, Mingxuan Ju, et al. "Disentangled Representation Learning in Heterogeneous Information Network for Large-scale Android Malware Detection in the COVID-19 Era and Beyond." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 9 (2021): 7754–61. http://dx.doi.org/10.1609/aaai.v35i9.16947.
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In the fight against the COVID-19 pandemic, many social activities have moved online; society's overwhelming reliance on the complex cyberspace makes its security more important than ever. In this paper, we propose and develop an intelligent system named Dr.HIN to protect users against the evolving Android malware attacks in the COVID-19 era and beyond. In Dr.HIN, besides app content, we propose to consider higher-level semantics and social relations among apps, developers and mobile devices to comprehensively depict Android apps; and then we introduce a structured heterogeneous information network (HIN) to model the complex relations and exploit meta-path guided strategy to learn node (i.e., app) representations from HIN. As the representations of malware could be highly entangled with benign apps in the complex ecosystem of development, it poses a new challenge of learning the latent explanatory factors hidden in the HIN embeddings to detect the evolving malware. To address this challenge, we propose to integrate domain priors generated from different views (i.e., app content, app authorship, app installation) to devise an adversarial disentangler to separate the distinct, informative factors of variations hidden in the HIN embeddings for large-scale Android malware detection. This is the first attempt of disentangled representation learning in HIN data. Promising experimental results based on the large-scale and real sample collections from security industry demonstrate the performance of Dr.HIN in evolving Android malware detection, by comparison with baselines and popular mobile security products.
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Shenigaram, Vidhya, Katakam Krishna Chaitanya, Pallavi Bhramarautu, and Mosheck Menta. "POPULARITY PREDICTION FOR SINGLE TWEET BASED ON HETEROGENEOUS BASS MODEL." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 9, no. 3 (2018): 1291–99. http://dx.doi.org/10.61841/turcomat.v9i3.14472.
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Predicting the popularity of a single tweet is useful for both users and enterprises. However, adopting existing topic or event prediction models cannot obtain satisfactory results. The reason is that one topic or event that consists of multiple tweets, has more features and characteristics than a single tweet. In this paper, we propose two variations of Heterogeneous Bass models (HBass), originally developed in the field of marketing science, namely Spatial-Temporal Heterogeneous Bass Model (ST-HBass) and Feature-Driven Heterogeneous Bass Model (FDHBass), to predict the popularity of a single tweet at the early stage and the stable stage. We further design an Interaction Enhancement to improve the performance, which considers the competition and cooperation from different tweets with the common topic. In addition, it is often difficult to depict popularity quantitatively. We design an experiment to get the weight of favorite, retweet and reply, and apply the linear regression to calculate the popularity. Furthermore, we design a clustering method to bound the popular threshold. Once the weight and popular threshold are determined, the status whether a tweet will be popular or not can be justified. Our model is validated by conducting experiments on real-world Twitter data, and the results show the efficiency and accuracy of our model, with less absolute percent error and the best Precision and F-score. In all, we introduce Bass model into social network single-tweet prediction to show it can achieve excellent performance.
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Metawa, Noura, and Maha Mutawea. "Multi-objective Decision Making Model for Stock Price Prediction Using Multi-source Heterogeneous Data Fusion." Fusion: Practice and Applications 9, no. 1 (2022): 59–69. http://dx.doi.org/10.54216/fpa.090105.
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Stock exchanges are developed as an essential component of economies, as they can promote financial and capital gain. The stock market is network of economic connections where share is bought and sold. Stock Market Prediction (SMP) is quite useful to investors. An effective forecast of stock prices is offer shareholders with suitable help in making appropriate decisions regarding if sell or purchase shares. The employ of Machine Learning (ML) and Sentiment Analysis (SA) on data in microblogging sites are developed as a famous approach to SMP. However, the heterogenous data fusion in stock market field is a big challenge. This paper introduces an effective Cat Swarm Optimization with Machine Learning Enabled Microblogging Sentiment Analysis for Stock Price Prediction technique. The presented model investigates the social media sentiments to foresee SPP. Firstly, the proposed model executes data pre-processing and Glove word embedding approach. Next, the weighted extreme learning machine approach was utilized for the classification of sentiments for SPP. Lastly, the CSO system was exploited for optimal adjustment of the parameters related to the WELM model. The experimental validation of the proposed approach was executed using microblogging data. The results show that the proposed method outperforms the previous studies.
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Sousa, Pedro Henrique Rodrigues de, Edgar Reyes Junior, Caroline Cordova Bicudo da Costa, and André Luiz Nascimento Reis. "Um modelo do processo de inovação à luz da Resource-Based View e da teoria do Crescimento da Firma, de Edith Penrose." Revista Ibero-Americana de Estratégia 20, no. 1 (2021): e19041. http://dx.doi.org/10.5585/riae.v20i1.19041.
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Objective: To analyze the innovation process in the light of the RBV and The Theory of the Growth of the Firm, by Edith Penrose.Methodology: A Systematic Literature Review was carried out using the Methodi Ordinatio. The Social Network Analysis technique was performed to determine which theoretical contexts the studies were based on. Similarity Analysis was also carried out to identify the relationship between the elements of the focal approaches and the innovation process.Originality/relevance: The Penrose study is considered by many researchers to be the antecedent of what was later called Resource-Based View, however, most of these studies did not fully explain the contribution of Penrose´s theory in the specifics of the theoretical view. Although research on innovation has been based on theoretical approaches in the field of strategy, there have been no analyses that systematized the innovation process by integrating the Penrose theory and RBV.Main results: The studies that analyzed innovation from the RBV and the Theory of the Growth of the Firm emphasized the maintenance of competitive advantage as a result of its dynamic capabilities, as well as access to and use of organizational knowledge.The authors identified heterogeneous innovation resources and imperfectly mobile, such as user-technology interactions, trajectory-dependent capabilities, specialized assets, RD capabilities, and network ties.Theoretical contributions: The study revealed that through the continuous execution of the innovation process, unique core competencies (e.g., RD experience) are developed to improve heterogeneous and imperfectly mobile innovation resources.
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Cârstea, Vlad Gabriel, Ana Maria Mihaela Iordache, Alexandru Ionescu, Nela Ramona Grigore, and Cristina Coculescu. "Enhancing Well-Being at Population Level: A Case Study on Romania." Sustainability 16, no. 23 (2024): 10497. http://dx.doi.org/10.3390/su162310497.
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The concept of well-being is multifaceted, influenced by a range of factors, including economic, social, perceptual, and personal, and varies considerably between individuals, countries, and continents. The objective of this research paper is to achieve an efficient grouping of countries according to several indicators that measure overall happiness. The indicators utilized in this study, derived from the World Happiness Report, are as follows: Life Ladder, Log GDP (Gross Domestic Product) per capita, Social Support, Healthy Life Expectancy at Birth, Freedom to Make Life Choices, Generosity, Perceptions of Corruption, Positive Affect, and Negative Affect. Consequently, following the identification, filtering, and collection of data on the countries in the study, cluster analysis, discriminant analysis, and neural network training were employed to obtain a classification of the countries into heterogeneous groups with a minimum error rate. Finally, for Romania, scenarios and policies were developed to facilitate ascent from the initial class to a class with a superior level of well-being.
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Savchuk, Galina A., Galina A. Bannykh, Sergey V. Kulpin, and Ruslan M. Kurashov. "Communication of Local Governments and the Population in Social Media: Regions of the Ural Federal District." Russian journal of regional studies 32, no. 4 (2024): 653–72. https://doi.org/10.15507/2413-1407.129.032.202404.653-672.
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Introduction. The relevance of the topic is determined by the need for a practical solution to the problem of communication assessment of local government bodies with the population in social media. The lack of an effective methodology for such an assessment and its results increases the importance of this work. The purpose of the article is to analyse the success of communication of the executive authorities of the municipal entities of the Ural Federal District with the population on the official pages of the social network “VKontakte” and to offer the success index. Materials and Methods. The authors used the database of official accounts of municipal, municipal district and municipal area administrations (n = 203) and heads of corresponding municipalities (n = 198) of the regions of the Urals Federal District in the social network “VKontakte”. The data were collected using the parsing tool Cerebro 3.0; the data were analyzed using both standard indicators of social network analysis and those proposed by the authors. The index method was used to summarize the data. This approach made it possible to systematize and aggregate heterogeneous information in order to compare the objects of analysis. Results. The authors have developed and tested on the materials of the regions of the Urals Federal District a methodology for calculating the index of success of communication between local governments and the population in the social network “VKontakte”. It has also been demonstrated that higher publication activity does not unequivocally lead to more successful communication outcomes. It is revealed that in most cases, municipalities with small populations are the most successful communicators. It is noted that subscriber engagement is higher in the accounts of heads of municipalities compared to the accounts of municipal administrations. Discussion and Conclusion. The authors’ proposed methodology for assessing the success of local government communications helps to identify the most successful practices, differentiate municipalities and regions. The index allows to go from evaluation of information openness to analysis of content published and recommendations on how to what content is needed to be more successful in communicating with the public. The results of the study will be useful for state and municipal employees involved in communication with the public.
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Rahmawati, Deti. "An Ecological-Oriented Policy Development Framework as An Alternative to Contesting Land-Oriented and Maritime-Oriented Paradigms." CosmoGov 7, no. 1 (2022): 18. http://dx.doi.org/10.24198/cosmogov.v7i1.28907.
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Two diverging geography-oriented Policy development paradigms have been prevailing within the discourse of Indonesian context, namely land and maritime-oriented paradigms. The two paradigms often emerge in ideological discourses that predispose national identity. Throughout the Indonesia’s history, discourses on development paradigms seems to alternate between two paradigms. However, since 2014, maritime paradigm has taken a dominant role in the Indonesian discourses.This paper propose empirical data associated with the environmental, economic and social conditions of Segara Anakan, Central of Java, we show how the land paradigm has resulted in undesirable consequences. Segara Anakan is a coastal region in which various communities have for decades developed economic activities. Major environmental damages in the region have been reported and social conflicts have occurred unresolved. Instead of choosing between land and maritime paradigms, in this paper we propose a more ecological-oriented development framework that is based on actor-network theory. we emphasis key measures: registering relevant heterogeneous entities, including human actors, social groups, small islands, straits, ocean inhabitants, etc; consultations that involve various spoke-persons. We argue in the paper that both land and maritime paradigms are too macro in their scope to tackle heterogeneities and complexities at the regional scopes.
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Danon, Leon, Lucas Lacasa, and Ellen Brooks-Pollock. "Household bubbles and COVID-19 transmission: insights from percolation theory." Philosophical Transactions of the Royal Society B: Biological Sciences 376, no. 1829 (2021): 20200284. http://dx.doi.org/10.1098/rstb.2020.0284.
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In the era of social distancing to curb the spread of COVID-19, bubbling is the combining of two or more households to create an exclusive larger group. The impact of bubbling on COVID-19 transmission is challenging to quantify because of the complex social structures involved. We developed a network description of households in the UK, using the configuration model to link households. We explored the impact of bubbling scenarios by joining together households of various sizes. For each bubbling scenario, we calculated the percolation threshold, that is, the number of connections per individual required for a giant component to form, numerically and theoretically. We related the percolation threshold to the household reproduction number. We find that bubbling scenarios in which single-person households join with another household have a minimal impact on network connectivity and transmission potential. Ubiquitous scenarios where all households form a bubble are likely to lead to an extensive transmission that is hard to control. The impact of plausible scenarios, with variable uptake and heterogeneous bubble sizes, can be mitigated with reduced numbers of contacts outside the household. Bubbling of households comes at an increased risk of transmission; however, under certain circumstances risks can be modest and could be balanced by other changes in behaviours. This article is part of the theme issue ‘Modelling that shaped the early COVID-19 pandemic response in the UK'.
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Sapaty, P. S. "Networking Solutions in Combined Distributed Worlds." Mathematical machines and systems 2 (2024): 33–48. http://dx.doi.org/10.34121/1028-9763-2024-2-33-48.
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The paper analyzes the rapidly growing importance of graph and network models and tools in such areas as transport, communications, social and military systems, goods production and distribution, education, economy, biology, psychology, criminology, climate change, etc. It aims at the development of effective methods capable of integrating different types of networks into higher-level infrastructures representing advanced social systems, particularly considering the symbiosis of goods production, goods evaluation, and the obtained product delivery systems under some universal networking concept. In a search for the latter, the article briefs the developed and patented Spatial Grasp Model and Technology (SGT) with its basic Spatial Grasp Language (SGL), which allow for fully distributed and parallel operations on arbitrary large and complex networked structures. The paper first shows some elementary networking operations in SGL useful for a better understanding of the rest of the material. Then it provides several practical examples of combined networking solutions, which include scenarios in SGL for finding the strongest production centers in their networks, as well as the most powerful user communities interested in and requesting particular types of products. After the selection of specific producers and consumers, the paper forms a distributed virtual and physical delivery infrastructure oriented on all of them and based on the shortest paths from producers to consumers and shows live the distribution process in SGL. The obtained results confirm that the deep integration of heterogeneous distributed systems can be organized naturally and automatically within the global integrity, awareness, and consciousness processes under the Spatial Grasp paradigm, as was already discussed in the previous publications on SGT.
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Pont, Polly C. A. Maclaine, and Hernán Thomas. "The Sociotechnical Alliance of Argentine Quality Wine." Science, Technology, & Human Values 37, no. 6 (2011): 627–52. http://dx.doi.org/10.1177/0162243911428623.
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Constructivist research in Science and Technology Studies (STS) is committed to revealing the heterogeneity of technological change and the fluid boundaries between the elements involved. Its major theories, the Social Construction of Technology (SCOT) and Actor Network Theory (ANT), have however both been criticized for limiting themselves to the micro-level of cases, impeding a structural analysis of technological systems. This article seeks to bridge any such divides. We research the recent changes in the viticulture of Mendoza, Argentina, which underwent radical changes over the past decades: once governed by low-cost yield maximization, grape production now revolves around “quality.” To show how the particular quality definition developed, we depart from a social-constructivist framework, following the sociotechnical shaping of problem-solution relationships across the wine production system. To include relevant social groups from different settings around the world, we gradually incorporate the ANT concepts of obligatory passage points, enrollment, convergence, delegation, and codes into the analysis. Combined into the concept of “sociotechnical alliance,” our analysis follows the dual process of creating agreement while establishing heterogeneous practices across settings at different levels. It shows that functioning involves alliance building and highlights the hybridity and continuous dynamics of systems at large.
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Mittal, Anuj, Nilufer Oran Gibson, Caroline C. Krejci, and Amy Ann Marusak. "Crowd-shipping for urban food rescue logistics." International Journal of Physical Distribution & Logistics Management 51, no. 5 (2021): 486–507. http://dx.doi.org/10.1108/ijpdlm-01-2020-0001.
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PurposeThe purpose of this research is to gain a better understanding of how a crowd-shipping platform can achieve a critical mass of senders and carrier crowd members to yield network effects that are necessary for the platform to grow and thrive. Specifically, this research studies the participation decisions of both senders and carriers over time and the impacts of the resulting feedback loop on platform growth and performance.Design/methodology/approachAn agent-based model is developed and used to study dynamic behavior and network effects within a simulated crowd-shipping platform. The model allows both carriers and senders to be represented as autonomous, heterogeneous and adaptive agents, whose decisions to participate in the platform impact the participation of other agents over time. Survey data inform the logic governing agent decisions and behaviors.FindingsThe feedback loop created by individual sender and carrier agents' participation decisions generates complex and dynamic network effects that are observable at the platform level. Experimental results demonstrate the importance of having sufficient crowd carriers available when the platform is initially launched, as well as ensuring that sender and carrier participation remains balanced as the platform grows over time.Research limitations/implicationsThe model successfully demonstrates the power of agent-based modeling (ABM) in analyzing network effects in crowd-shipping systems. However, the model has not yet been fully validated with data from a real-world crowd-shipping platform. Furthermore, the model's geographic scope is limited to a single census tract. Platform behavior will likely differ across geographic regions, with varying demographics and sender/carrier density.Practical implicationsThe modeling approach can be used to provide the manager of a volunteer-based crowd-shipping program for food rescue with insights on how to achieve a critical mass of participants, with an appropriate balance between the number of restaurant food donation delivery requests and the number of crowd-shippers available and willing to make those deliveries.Social implicationsThis research can help a crowd-shipping platform for urban food rescue to grow and become self-sustainable, thereby serving more food-insecure people.Originality/valueThe model represents both senders and the carrier crowd as autonomous, heterogeneous and adaptive agents, such that network effects resulting from their interactions can emerge and be observed over time. The model was designed to study a volunteer crowd-shipping platform for food rescue, with participant motivations driven by personal values and social factors, rather than monetary incentives.
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Marzook, Mahmoud, and Bassam Al Ahmady. "Linking Organisational Performance and Corporate Social Responsibility." European Journal of Business and Management Research 7, no. 3 (2022): 335–43. http://dx.doi.org/10.24018/ejbmr.2022.7.3.1466.
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Purpose: Business organisations are at the core of sustainable development, and they can be no longer isolated from social concerns and issues where they operate and exist. While many firms have applied CSR practices successfully and made it fruitful for both business and society, many others are still struggling as no one strategy can usually fit all and CSR initiatives does not promise the same payoffs among different companies and sectors. In this context, the study aims to examine the link between organisational performance and CSR and provide a milestone that would help business organisations to successfully apply CSR initiatives. Design/methodology/approach: Drawing upon field research, 378 questionnaires were collected from various managerial and non-managerial employees of the mobile network operators in Egypt to examine the research hypotheses. Findings: Extending the relation between organisational performance and CSR, this paper demonstrates the heterogeneous ways in which organisational performance can be a key determinant for being engaged in successful CSR initiatives. It argued how organisational performanceــmaterialised in integrating business-related social issues into the organisational strategy, financial performance, CSR capability responsiveness, and social performanceــ can help business organisation establish a win-win situation and create a business-society shared value. Research limitations/implications: The research focuses on four business organisations operating as mobile network service providers in Egypt. Practical implications: The research findings have important implications, more specifically, for firms willing to engage for successful CSR practices, and how social issues and concerns can be translated into business opportunities to motivate business organisations to address them. Social implications: CSR is still controversial to a great extent; especially from an empirical perspective in less developed and developing countries like Egypt, where environmental and social considerations are limited; regarded as a task to be done by a few (Gov., NGOs, NPO, etc.); and where CSR activities are carried through philanthropic perspective. This research implies the possibility to look at social issues and concerns as an opportunity for strategic CSR that create a shared value for business and society and formulate a win-win situation. Originality/value: This paper’s contribution is threefold. First, theoretically, the literature on organisational performance and CSR is extended by considering how they can complement one another. The nuanced focus on this relation provides a “zoom in” that organisational performance is a key success factor while considering CSR. Second, the literature on shared value is deepened by identifying a diverse range of imbricating logics that can be used to discern a more nuanced connection between business and society. Last, these ideas are grounded in a relevant field study context –that of CSR activities in Egypt–, providing more knowledge, over time, of specific actors’ translations of CSR policies into business organisations’ strategies and practices.
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КАШТАЛЬЯН, АНТОНІНА. "МУЛЬТИКОМП’ЮТЕРНА СИСТЕМА З КОМБІНОВАНИХ АНТИВІРУСНИХ ПРИМАНОК І ПАСТОК ДЛЯ ВИЯВЛЕННЯ ЗЛОВМИСНОГО ПРОГРАМНОГО ЗАБЕЗПЕЧЕННЯ ТА КОМП’ЮТЕРНИХ АТАК НА ОСНОВІ МУЛЬТИАГЕНТНИХ ТЕХНОЛОГІЙ". Herald of Khmelnytskyi National University. Technical sciences 347, № 1 (2025): 535–42. https://doi.org/10.31891/2307-5732-2025-347-73.
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The work has a comprehensive approach to protecting the computer by creating a network of baits, which ensures effective detection of malicious traffic and analysis of new attacks. An innovative system is introduced, which includes baits capable of monitoring exclusively hostile traffic, which can significantly reduce the response time to potential threats and ensures high detection of attacks on the network. A multi -agent bait system is implemented, which combines a set of heterogeneous baits, each of which performs certain functions aimed at counteracting threats. Highly effective intellectual lures have been developed, which have the properties of autonomous agents and are characterized by adaptive behavior, which enables them to respond quickly and effectively to changes in the network environment. They are able to independently determine the features of attacks, adapt their behavior to threats and transmit relevant information to other components of the system, which significantly increases the efficiency of the entire network of baits. The integration of key characteristics, such as reactivity, proactivity and social interaction of baits, is ensured. Reactivity is realized through the ability to analyze the environment, respond in a timely manner to change network traffic and adapt quickly to new attacks. Proactivity provides the possibility of baits not only to respond to existing threats, but also to anticipate potential attacks, modeling the behavior of the intruders and accordingly changing their work algorithms. The social capabilities of the developed system allow the lures to interact, exchange information about potential threats, coordinate actions and form a single network protection strategy. This implemented a flexible, adaptive and effective cybersecurity system that not only protects the network from attacks, but also actively studies the behavioral models of malefactors. The multi -computer system is deployed, which includes baits and traps integrated at the corporate network nodes. This allows you to create a scaled environment for comprehensive threat analysis and effective risk management. Thanks to the modular approach, both centralized and decentralized architecture of the multi -gault system of baits have been implemented. In the centralized version, all collected data are transmitted to the central device of the network, where their comprehensive analysis is carried out, including statistical and behavioral. For this purpose, a data collection, processing and correlation system has been developed, which allows you to get a holistic picture of cyber threats in the network. On the basis of these data, the mechanism of training of machine learning models is implemented that allow you to predict potential attack vectors and automatically adapt the security system to new threats. A flexible bait management system is introduced, which makes it easy to change the parameters of work, adapt the behavior of individual elements of the network and respond promptly to new threats. The whole system operates in constant self -study mode, which allows it to improve the algorithms of work without administrator intervention. This has created a dynamic corporate network protection system that is capable not only of real -time threats, but also proactively prevent potential attacks.
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Sumiala, Johanna, Minttu Tikka, Jukka Huhtamäki, and Katja Valaskivi. "#JeSuisCharlie: Towards a Multi-Method Study of Hybrid Media Events." Media and Communication 4, no. 4 (2016): 97–108. http://dx.doi.org/10.17645/mac.v4i4.593.
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This article suggests a new methodological model for the study of hybrid media events with global appeal. This model, developed in the project on the 2015 <em>Charlie Hebdo</em> attacks in Paris, was created specifically for researching digital media—and in particular, Twitter. The article is structured as follows. Firstly, the methodological scope is discussed against the theoretical context, e.g. the theory of media events. In the theoretical discussion, special emphasis is given to i) disruptive, upsetting, or disintegrative media events and hybrid media events and ii) the conditions of today’s heterogeneous and globalised media communication landscape. Secondly, the article introduces a multi-method approach developed for the analysis of hybrid media events. In this model, computational social science—namely, automated content analysis (ACA) and social network analytics (SNA)—are combined with a qualitative approach—specifically, digital ethnography. The article outlines three key phases for research in which the interplay between quantitative and qualitative approaches is played out. In the first phase, preliminary digital ethnography is applied to provide the outline of the event. In the second phase, quantitative social network analytics are applied to construct the digital field for research. In this phase, it is necessary to map a) what is circulating on the websites and b) where this circulation takes place. The third and final phase applies a qualitative approach and digital ethnography to provide a more nuanced, in-depth interpretation of what (substance/content) is circulating and how this material connects with the ‘where’ in the digital landscape, hence constituting links and connections in the hybrid media landscape. In conclusion, the article reflects on how this multi-method approach contributes to understanding the workings of today’s hybrid media events: how they create and maintain symbolic battles over certain imagined constructs of social imaginaries of solidarity, belonging, contestation, and exclusion, a topic of core value for the theory of media events.
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Horianskyi, Serhii. "PHILOSOPHICAL ANALYSIS OF THE DEVELOPMENT OF IT EDUCATION IN UKRAINE THROUGH THE PRISM OF THE ACTOR-NETWORK THEORY OF BRUNO LATOUR." Educational Discourse: collection of scientific papers, no. 50(7-9) (September 10, 2024): 35–41. https://doi.org/10.33930/ed.2019.5007.50(7-9)-5.
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. The development of IT education in Ukraine is an important aspect of modern educational policy since the integration of information technologies into the educational process contributes to the improvement of the quality of education, provides access to the latest knowledge and technologies, and also prepares students for the challenges of the digital era. However, this process is complex and multifaceted, requiring considering both technical and philosophical, sociological, and ethical aspects. Actor-network theory, developed by Bruno Latour and his colleagues, offers an approach to analyzing social phenomena through the interaction between human and non-human actors, considering them elements of a heterogeneous network. The development of IT education in Ukraine must be carried out in compliance with the principles of ethics and inclusiveness. Conclusions. Based on research and publications, several key examples of successful integration of IT technologies into the educational process in Ukraine can be identified. The introduction of online platforms for distance learning during the COVID-19 pandemic and war to ensure the continuity of the educational process. Another example is the development of projects such as the educational platform “Diia. Education” and “Mriya”, MOOC “Prometheus” and others. It aims to improve digital literacy among teachers and students, improving education quality and accessibility.
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Calvetti, Daniela, Alexander P. Hoover, Johnie Rose, and Erkki Somersalo. "Modeling Epidemic Spread among a Commuting Population Using Transport Schemes." Mathematics 9, no. 16 (2021): 1861. http://dx.doi.org/10.3390/math9161861.
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Understanding the dynamics of the spread of COVID-19 between connected communities is fundamental in planning appropriate mitigation measures. To that end, we propose and analyze a novel metapopulation network model, particularly suitable for modeling commuter traffic patterns, that takes into account the connectivity between a heterogeneous set of communities, each with its own infection dynamics. In the novel metapopulation model that we propose here, transport schemes developed in optimal transport theory provide an efficient and easily implementable way of describing the temporary population redistribution due to traffic, such as the daily commuter traffic between work and residence. Locally, infection dynamics in individual communities are described in terms of a susceptible-exposed-infected-recovered (SEIR) compartment model, modified to account for the specific features of COVID-19, most notably its spread by asymptomatic and presymptomatic infected individuals. The mathematical foundation of our metapopulation network model is akin to a transport scheme between two population distributions, namely the residential distribution and the workplace distribution, whose interface can be inferred from commuter mobility data made available by the US Census Bureau. We use the proposed metapopulation model to test the dynamics of the spread of COVID-19 on two networks, a smaller one comprising 7 counties in the Greater Cleveland area in Ohio, and a larger one consisting of 74 counties in the Pittsburgh–Cleveland–Detroit corridor following the Lake Erie’s American coastline. The model simulations indicate that densely populated regions effectively act as amplifiers of the infection for the surrounding, less densely populated areas, in agreement with the pattern of infections observed in the course of the COVID-19 pandemic. Computed examples show that the model can be used also to test different mitigation strategies, including one based on state-level travel restrictions, another on county level triggered social distancing, as well as a combination of the two.
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Hagoel, Lea, Gad Rennert, and Efrat Neter. "Translational Research in Cancer Screening: Long-Term Population-Action Bridges to Diffuse Adherence." International Journal of Environmental Research and Public Health 18, no. 15 (2021): 7883. http://dx.doi.org/10.3390/ijerph18157883.
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The population-level implementation of innovative, evidence-based medical recommendations for adopting health-behaviors depends on the last link in the translation chain: the users. “User-friendly” medical interventions aimed at engaging users to adopt recommended health behaviors are best developed in a collaborative bio-medical and social sciences setting. In the 1990s, National Breast and Colorectal Cancer Early Detection Programs were launched at the Israeli Department of Community Medicine and Epidemiology. Operating under the largest HMO (Health Maintenance Organization) in Israel (“Clalit Health Services”), the department had direct access to HMO community primary-care clinics’ teams, insured members, and medical records. Academically affiliated, the department engaged in translational research. In a decades-long translational process, this multi-disciplinary unit led a series of interventions built upon basic and applied behavioral/social science phenomena such as framing, “Implementation Intentions,” and “Question-Behavior-Effect”. A heterogeneous team of disciplinary specialists created an integrated scientific environment. In order to enhance screening, the team focused on the establishment of a systematic mechanism actively inviting programs’ “users” (average-risk targeted individuals on the national level), and continuously applied social and health psychology concepts to study individuals’ perceptions, expectations, and needs related to cancer screening. The increase in adherence to screening recommendations was slow and incremental. A decrease in late-stage breast and colorectal cancer diagnoses was observed nationally, but participation was lower than expected. This paper positions screening adherence as a unique challenge and proposes new social and network avenues to enhance future participation.
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Moustakidis, Serafeim, Ioannis Meintanis, Nicos Karkanias, et al. "Innovative Technologies for District Heating and Cooling: InDeal Project." Proceedings 5, no. 1 (2019): 1. http://dx.doi.org/10.3390/proceedings2019005001.
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The paper discusses the outcomes of the conference organized by the InDeal project. The conference took place on 12 December 2018 in Montpellier as part of the EnerGaia energy forum 2018. A holistic interdisciplinary approach for district heating and cooling (DHC) networks is presented that integrates heterogeneous innovative technologies from various scientific sectors. The solution is based on a multi-layer control and modelling framework that has been designed to minimize the total plant production costs and optimize heating/cooling distribution. Artificial intelligence tools are employed to model uncertainties associated with weather and energy demand forecasts, as well as quantify the energy storage capacity. Smart metering devices are utilized to collect information about all the crucial heat substations’ parameters, whereas a web-based platform offers a unique user environment for network operators. Three new technologies have been further developed to improve the efficiency of pipe design of DHC systems: (i) A new sustainable insulation material for reducing heat losses, (ii) a new quick-fit joint for an easy installation, and (iii) a new coating for reducing pressure head losses. The results of a study on the development and optimization of two energy harvesting systems are also provided. The assessment of the environmental, economic and social impact of the proposed holistic approach is performed through a life cycle analysis. The validation methodology of the integrated solution is also described, whereas conclusions and future work are finally given.
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Sauri Pujol, David, and Noemi Baldino. "Characterizing the recent decline of water consumption in Italian cities." Investigaciones Geográficas, no. 69 (June 13, 2018): 9. http://dx.doi.org/10.14198/ingeo2018.69.01.
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There is increasingly more evidence showing that domestic water consumption is decreasing in many urban areas of the developed world. A large and heterogeneous set of factors may explain this decrease, ranging from structural phenomena, such as changes in the composition of urban populations or in the economic basis of cities to the implementation of more conscious policies such as technological improvements; citizen awareness or higher water prices and taxes. In this paper we examine the drop in water consumption for the ten largest Italian cities. The Italian water sector is characterized by a highly fragmented governance structure that results in a significantly inefficient distribution network, which might be highly exposed to the effects of climate change. However, there is strong opposition to privatization. In the paper we document the drop in water consumption in the largest Italian cities showing demographic (aging), social (migration) and economic (income) factors at the same time. Although it is unlikely that one single reason can explain the declining trend, our conclusion points to a combination of structural factors and specific policies that seem to be more intense in the Northern and Central cities than in the Southern cities.
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., Anil Kumar. "EVOLUTION OF SOCIAL DEVELOPER NETWORK IN OSS: SURVEY." International Journal of Research in Engineering and Technology 03, no. 04 (2014): 412–16. http://dx.doi.org/10.15623/ijret.2014.0304074.
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Rolls, Kaye Denise, Margaret Mary Hansen, Debra Jackson, and Doug Elliott. "Why Health Care Professionals Belong to an Intensive Care Virtual Community: Qualitative Study." Journal of Medical Internet Research 21, no. 11 (2019): e14068. http://dx.doi.org/10.2196/14068.
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Background Clinical practice variation that results in poor patient outcomes remains a pressing problem for health care organizations. Some evidence suggests that a key factor may be ineffective internal and professional networks that limit knowledge exchange among health care professionals. Virtual communities have the potential to overcome professional and organizational barriers and facilitate knowledge flow. Objective This study aimed to explore why health care professionals belong to an exemplar virtual community, ICUConnect. The specific research objectives were to (1) understand why members join a virtual community and remain a member, (2) identify what purpose the virtual community serves in their professional lives, (3) identify how a member uses the virtual community, and (4) identify how members used the knowledge or resources shared on the virtual community. Methods A qualitative design, underpinned by pragmatism, was used to collect data from 3 asynchronous online focus groups and 4 key informant interviews, with participants allocated to a group based on their posting behaviors during the previous two years—between September 1, 2012, and August 31, 2014: (1) frequent (>5 times), (2) low (≤5 times), and (3) nonposters. A novel approach to focus group moderation, based on the principles of traditional focus groups, and e-moderating was developed. Thematic analysis was undertaken, applying the Diffusion of Innovation theory as the theoretical lens. NCapture (QRS International) was used to extract data from the focus groups, and NVivo was used to manage all data. A research diary and audit trail were maintained. Results There were 27 participants: 7 frequent posters, 13 low posters, and 7 nonposters. All participants displayed an external orientation, with the majority using other social media; however, listservs were perceived to be superior in terms of professional compatibility and complexity. The main theme was as follows: “Intensive care professionals are members of ICUConnect because by being a member of a broader community they have access to credible best-practice knowledge.” The virtual community facilitated access to all professionals caring for the critically ill and was characterized by a positive and collegial online culture. The knowledge found was credible because it was extensive and because the virtual community was moderated and sponsored by a government agency. This enabled members to benchmark and improve their unit practices and keep up to date. Conclusions This group of health care professionals made a strategic decision to be members of ICUConnect, as they understood that to provide up-to-date clinical practices, they needed to network with colleagues in other facilities. This demonstrated that a closed specialty-specific virtual community can create a broad heterogeneous professional network, overcoming current ineffective networks that may adversely impact knowledge exchange and creation in local practice settings. To address clinical practice variation, health care organizations can leverage low-cost social media technologies to improve interprofessional and interorganizational networks.
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Herbold, Steffen, Aynur Amirfallah, Fabian Trautsch, and Jens Grabowski. "A systematic mapping study of developer social network research." Journal of Systems and Software 171 (January 2021): 110802. http://dx.doi.org/10.1016/j.jss.2020.110802.
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Zaitseva, Nina V., Svetlana V. Kleyn, Maxim V. Glukhikh, and Marat R. Kamaltdinov. "ON ASSESSING THE GROWTH POTENTIAL OF THE LIFE EXPECTANCY OF THE POPULATION AS A RESULT OF IMPLEMENTING INTEGRATED MEASURES (ON THE EXAMPLE OF A CONSTITUENT ENTITY OF THE RUSSIAN FEDERATION)." Siberian Journal of Life Sciences and Agriculture 15, no. 6 (2023): 267–87. http://dx.doi.org/10.12731/2658-6649-2023-15-6-988.
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The development vector of the current government policy in the Russian Federation aimed at improving social conditions – one of the critical indicators of which is life expectancy at birth [LE] – dictates the research relevance. Currently, the search and testing of new analytical systems capable of forecasting LE, considering the multifactorial influence on this indicator, remains relevant and timely. The research goal is to establish the growth potential of LE of the population estimation on the example of one of the constituent entities of the Russian Federation, considering integrated heterogeneous factors that possess a modifying effect on LE. The estimation includes modeling cause-and-effect relationships between indicators of habitat, quality of life, and life patterns – determinants of population health. The utilized model is a set of algebraic equations in the form of a factor transformation of independent variables and an artificial neural network and is implemented in three stages. They include (1) developing the basic scenario and calculating LE, (2) developing the target scenario and calculating LE, and (3) calculating the growth potential of LE as the difference between the indicators obtained at previous stages. The developed model and the three-stage algorithm application allows one to obtain the growth potential of LE on the example of one constituent entity of the Russian Federation in the context of a single change in determinants by 2024, which amounts to +1.24 years (453.0 days) relative to the baseline scenario (the actual LE value in 2018). The forecast value of LE is 70.47 years. Ranking of individual indicator groups according to their isolated effect on LE demonstrates that the most significant determinant groups are (1) socio-demographic indicators (2.6 years – 949.0 days), (2) indicators of sanitary and epidemiological safety (1.75 years – 638.75 days), and the (3) population lifestyle indicators (1.41 years – 514.65 days). The obtained results confirm the predominance of the influence of social indicators on population health in the form of LE on the example of the analysis of changes in the indicators of one of the constituent entities of the Russian Federation. The research relevance implies studying the combined influence of heterogeneous factors of the environment and lifestyle on the indicative indicator of population health (LE), a complex system with the properties of emergence, variability, opposite influence, and adaptation.
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Paladin, Zdravko, Nexhat Kapidani, Alkiviadis Astyakopoulos, et al. "Maritime information sharing environment deployment using the advanced multilayered Data Lake capabilities." Pomorstvo 36, no. 2 (2022): 291–304. http://dx.doi.org/10.31217/p.36.2.13.
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Establishing an efficient information sharing network among national agencies in maritime domain is of essential importance in enhancing the operational performance, increasing the situational awareness and enabling interoperability among all involved maritime surveillance assets. Based on various data-driven technologies and sources, the EU initiative of Common Information Sharing Environment (CISE), enables the networked participants to timely exchange information concerning vessel traffic, joint SAR & operational missions, emergency situations and other events at sea. In order to host and process vast amounts of vessels and related maritime data consumed from heterogeneous sources (e.g. SAT-AIS, UAV, radar, METOC), the deployment of big data repositories in the form of Data Lakes is of great added value. The different layers in the Data Lakes with capabilities for aggregating, fusing, routing and harmonizing data are assisted by decision support tools with combined reasoning modules with semantics aiming at providing a more accurate Common Operational Picture (COP) among maritime agencies. Based on these technologies, the aim of this paper is to present an end-to-end interoperability framework for maritime situational awareness in strategic and tactical operations at sea, developed in EFFECTOR EU-funded project, focusing on the multilayered Data Lake capabilities. Specifically, a case study presents the important sources and processing blocks, such as the SAT-AIS, CMEMS, UAV components, enabling maritime information exchange in CISE format and communication patterns. Finally, the technical solution is validated in the project’s recently implemented maritime operational trials and the respective results are documented.
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Peng, Cheng Xiang. "An Empirical Analysis of Developer Collaboration Network." Applied Mechanics and Materials 303-306 (February 2013): 2177–81. http://dx.doi.org/10.4028/www.scientific.net/amm.303-306.2177.
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To further verify the uses of bipartite network theory and understand the intrinsic nature in social collaboration network. In this paper, we get the information of open source software projects from Source-Forge web and construct a project management collaboration network by analyzing the data of project and manager. Then, through the ordinary projection two kinds of one-mode network are made and the degree distribution of one-mode network and origin bipartite networks shows a power-law like. Finally we evaluate the node's importance on manager network to acquire the core nodes, namely domain experts, by using the metric of node degree, between and topological potential respectively, and provide some helpful applications.
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Niles, Meredith T., Serge Wiltshire, Jason Lombard, et al. "Manure management strategies are interconnected with complexity across U.S. dairy farms." PLOS ONE 17, no. 6 (2022): e0267731. http://dx.doi.org/10.1371/journal.pone.0267731.
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Among one of the key challenges in dairy production is the management of manure in a way that is beneficial for agricultural production, with minimal environmental and public health impacts. Manure management systems (MMS)—the entire system of handling, storage, and application of manure—are diverse in countries with developed dairy industries such as the United States, enabled by a number of different technologies. The ways in which dairy farmers manage manure is driven by varying tradeoffs, including economic, social, and environmental; however, existing research has not examined the relationships between components of MMS. Here we use data from the National Animal Health Monitoring System’s Dairy 2014 study to explore the ways in which manure handling, storage, and application are related, using a series of logistic regression models and network associations. We found significant associations between how manure is handled, stored, and applied, especially driven by the consistency of manure. For solid manure, we found highly heterogeneous systems, where farmers may have a suite of alternative manure management strategies available to them, and substitution is viable. Conversely, farms using liquid manure systems have very few substitutes in their MMS, suggesting greater investment in certain infrastructures, which are not easily changed. Such findings have important implications for shifting farmers towards management practices with minimal environmental and public health impacts, demonstrating that not all farm systems are easily changed. We highlight these results in light of current policies, which may not fully capture the relationships across the MMS, and suggest that greater financing may be necessary to shift MMS on some farms. Furthermore, we suggest that different MMS have varying tradeoffs across environmental, social, and economic aspects, which demonstrates that MMS are highly individualized to a given farm’s goals and priorities.
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Liu, Baochuan, Li Zhang, Zhenwei Liu, and Jing Jiang. "Developer Assignment Method for Software Defects Based on Related Issue Prediction." Mathematics 12, no. 3 (2024): 425. http://dx.doi.org/10.3390/math12030425.
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The open-source software platform hosts a large number of software defects, and the task of relying on administrators to manually assign developers is often time consuming. Thus, it is crucial to determine how to assign software defects to appropriate developers. This paper presents DARIP, a method for assigning developers to address software defects. First, the correlation between software defects and issues is considered, predicting related issues for each defect and comprehensively calculating the textual characteristics of the defect using the BERT model. Second, a heterogeneous collaborative network is constructed based on the three development behaviors of developers: reporting, commenting, and fixing. The meta-paths are defined based on the four collaborative relationships between developers: report–comment, report–fix, comment–comment, and comment–fix. The graph-embedding algorithm metapath2vec extracts developer characteristics from the heterogeneous collaborative network. Then, a classifier based on a deep learning model calculates the probability assigned to each developer category. Finally, the assignment list is obtained according to the probability ranking. Experiments on a dataset of 20,280 defects from 9 popular projects show that the DARIP method improves the average of the Recall@5, the Recall@10, and the MRR by 31.13%, 21.40%, and 25.45%, respectively, compared to the state-of-the-art method.
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Kniazevych, Anna, Volodymyr Olikhovskyi, and Marta Olikhovska. "CLUSTERING OF THE ECONOMY AS A MEANS OF DEVELOPING AN INNOVATION INFRASTRUCTURE." Baltic Journal of Economic Studies 7, no. 3 (2021): 134–39. http://dx.doi.org/10.30525/2256-0742/2021-7-3-134-139.
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The experience of the functioning of national innovation systems in the developed countries indicates that the development of an innovative model of the national economy is impossible without the formation of an active innovation infrastructure. The article deals with the problems of formation and development of the innovation infrastructure of the country in difficult social and economic conditions based on clustering of the economy. The purpose of the research is to analyze the role and impact of clusters on self-organization and self-development of the country’s innovation infrastructure in the conditions of limited financial resources. The research investigates the tendencies of the spread of regional clustering and its influence on the creation of a network of infrastructure companies, which, on a commercial basis, offer and distribute services. Clustering of regions is accompanied by the spread of the impact of a growing number of clusters (innovation structures of the network type) on the national economy and its innovation infrastructure. A certain infrastructural environment develops around the hub and the core of the cluster. It includes a number of companies specializing in innovative services, which can offer their services on a commercial basis not only to companies in this cluster, but also to all nearby innovative enterprises. The spread of clustering in all regions can serve as a basis for further self-organization and self-development of subsidiary companies under the influence of market mechanisms of management and growth of the innovation infrastructure of clusters into a basic platform of the innovation infrastructure of the country. Activation of entrepreneurship in clusters is carried out through the concentration of business activity and inter-sectoral cooperation. Vertical cluster associations are formed based on the synergy of enterprises, institutions, organizations, and individuals that are heterogeneous in the field of activity and form of ownership. The state, creating a favorable innovation environment, regulates the boundary conditions for innovation infrastructure subjects and clusters, which independently self-organize themselves under the influence of market mechanisms and expand their services to all regions, forming a holistic innovation infrastructure of the country.