Gotowe bibliografie tematyczne / Social networl analysis

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Gotowa bibliografia na temat „Social networl analysis”

Autor: Grafiati

Data publikacji: 2 czerwca 2025

Data aktualizacji: 22 czerwca 2025

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Artykuły w czasopismach na temat "Social networl analysis"

Reis, Eduardo, Magno José Alves, Camilo Dias Seabra, et al. "Socio-environmental assessment of the Santos and São Vicente municipalities on the coast of São Paulo/Brazil: application of social network analysis to the DPSIR conceptual framework." Revista Processando o Saber 17, no. 01 (2025): 261–78. https://doi.org/10.5281/zenodo.15499049.

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Considering the social, economic, and ecological complexity of coastal regions and the difficulty of public and private environmental management in these highly populated areas with multiple sources of pollution, this study used the driver, pressure, state, impact, and response model to socio-environmentally assess the coastal municipalities of Santos and São Vicente in the Baixada Santista metropolitan region, SP-Brazil. Data were evaluated by social network analysis. Results indicated the most relevant drivers (i.e., those that most affected sustainability and environmental governance) within the municipalities of Santos and São Vicente, such as port activities (represented by the pressure due to the emission of contaminants in the air and water and dredging). Poor air quality due to pollution and its impacts on human health stand out as an element in the state factor. The most forceful responses refer to the increase in the inspection and control of atmospheric emissions, liquid effluents, dredging, and solid waste. Our approach will support decision-makers to focus on the most critical aspects in this study to implement corrective and preventive actions and develop environmental and sectoral public policies.

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Jadhav, Pranavati, and Dr Burra Vijaya Babu. "Detection of Community within Social Networks with Diverse Features of Network Analysis." Journal of Advanced Research in Dynamical and Control Systems 11, no. 12-SPECIAL ISSUE (2019): 366–71. http://dx.doi.org/10.5373/jardcs/v11sp12/20193232.

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Shcherbakov, V. S., and I. A. Karpov. "Regional Inflation Analysis Using Social Network Data." Economy of Regions 20, no. 3 (2024): 930–46. http://dx.doi.org/10.17059/ekon.reg.2024-3-21.

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Inflation is one of the most important macroeconomic indicators that have a great impact on the population of any country and region. Inflation is influenced by a range of factors, including inflation expectations. Many central banks take this factor into consideration while implementing monetary policy within the inflation targeting regime. Nowadays, a lot of people are active users of the Internet, especially social networks. It is hypothesised that people search, read, and discuss mainly only those issues that are of particular interest to them. It is logical to assume that the dynamics of prices may also be in the focus of users’ discussions. So, such discussions could be regarded as an alternative source of more rapid information about inflation expectations. This study is based on unstructured data from VKontakte social network used to analyse upward and downward inflationary trends (on the example of the Omsk region). The sample of more than 8.5 million posts was collected between January 2010 and May 2022. The authors used BERT neural networks to solve the problem. These models demonstrated better results than the benchmarks (e.g., logistic regression, decision tree classifier, etc.). It makes possible to define pro-inflationary and disinflationary types of keywords in different contexts and get their visualisation with SHAP method. This analysis provides additional operational information about inflationary processes at the regional level The proposed approach can be scaled for other regions. At the same time, the limitation of the work is the time and power costs for the initial training of similar models for all regions of Russia.

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Almahmoud, Essam, and Hemanta Kumar Doloi. "Assessment of Social Sustainability in Construction Projects Using Social Network Analysis." JOURNAL OF INTERNATIONAL BUSINESS RESEARCH AND MARKETING 3, no. 6 (2018): 35–46. http://dx.doi.org/10.18775/jibrm.1849-8558.2015.36.3003.

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This paper aims to propose a framework that puts the stakeholders at the forefront of achieving sustainability in the social context. This research, thus, argues that the social sustainability outcomes in construction are best achieved by taking into account the satisfaction of the stakeholders. Based on sustainability and equity theories, a dynamic assessment model has been developed to evaluate the contributions of projects in a social context. Multiple stakeholders and their differing interests associated with the construction projects have been integrated using social network analysis. The mapping of the relationships between the project stakeholders, with respect to their relative stakes and seven social core functions, have been integrated into the assessment model. The findings of this research suggest that the degree of satisfying the needs of diverse stakeholders is highly significant in achieving social sustainability performance of projects. Using a case study from Saudi Arabia, the applicability and significance of the assessment model has been demonstrated. The application of the model provides the opportunity to identify any problems and to enhance the overall performance of projects in the social context. The functionality and efficacy of the model need to be further tested outside the Saudi Arabian region. The research is original in the sense that for the first time, a novel approach has been developed, putting the stakeholders at the forefront of achieving sustainability outcomes in construction projects

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S., Geetha. "Big Data Analysis - Cybercrime Detection in Social Network." Journal of Advanced Research in Dynamical and Control Systems 12, SP4 (2020): 147–52. http://dx.doi.org/10.5373/jardcs/v12sp4/20201476.

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Ashlesha, S. Nagdive, Tugnayat Rajkishor, and Peshkar Atharva. "Social Network Analysis of Terrorist Networks." International Journal of Engineering and Advanced Technology (IJEAT) 9, no. 3 (2020): 2553–59. https://doi.org/10.35940/ijeat.C5431.029320.

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Terrorist Activities worldwide has led to the development of sophisticated methodologies for analyzing terrorist groups and networks. Ongoing and past research has found that Social Network Analysis (SNA) is most effective method for predictive counter-terrorism. Social Network Analysis (SNA) is an approach towards analyzing the terrorist networks to better understand the underlying structure of a network and to detect key players within the network and their links throughout the network. It is also need of the hour to convert available raw data into valuable information for the purpose of global security. Comparative study among SNA tools testify their applicability and usefulness for data gathered through online and offline social sources. However it is advised to incorporate temporal analysis using data mining methods, to improve the capability of SNA tools to handle dynamic social media data. This paper examine various aspects of Social Network Analysis as applied to terrorism, taking empirical data, and open source data based studies into account. This work primarily focuses on different types of decentralized terrorist networks and nodes. The nodes can be classified as organizations, places or persons. We take help of varied centrality measures to identify key players in this network.

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Del Fresno García, Miguel. "Connecting the Disconnected: Social Work and Social Network Analysis. A Methodological Approach to Identifying Network Peer Leaders." Arbor 191, no. 771 (2015): a209. http://dx.doi.org/10.3989/arbor.2015.771n1011.

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Nasution, Mahyuddin K. M., Rahmad Syah, and Marischa Elveny. "Social Network Analysis: Towards Complexity Problem." Webology 18, no. 2 (2021): 449–61. http://dx.doi.org/10.14704/web/v18i2/web18332.

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Social network analysis is a advances from field of social networks. The structuring of social actors, with data models and involving intelligence abstracted in mathematics, and without analysis it will not present the function of social networks. However, graph theory inherits process and computational procedures for social network analysis, and it proves that social network analysis is mathematical and computational dependent on the degree of nodes in the graph or the degree of social actors in social networks. Of course, the process of acquiring social networks bequeathed the same complexity toward the social network analysis, where the approach has used the social network extraction and formulated its consequences in computing.

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Davel, Ronel, Adeline S. A. Du Toit, and Martie M. Mearns. "Understanding Knowledge Networks Through Social Network Analysis." International Journal of Knowledge Management 13, no. 2 (2017): 1–17. http://dx.doi.org/10.4018/ijkm.2017040101.

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Social network analysis (SNA) is being increasingly deployed as an instrument to plot knowledge and expertise as well as to confirm the character of connections in informal networks within organisations. This study investigated how the integration of networking into KM can produce significant advantages for organisations. The aim of the research was to examine how the interactions between SNA, Communities of Practice (CoPs) and knowledge maps could potentially influence knowledge networks. The researchers endeavour to illustrate via this question that cultivating synergies between SNA, CoPs and knowledge maps will enable organisations to produce stronger knowledge networks and ultimately increase their social capital. This article intends to present a process map that can be useful when an organisation wants to positively increase its social capital by examining influencing interactions between SNA, CoPs and knowledge maps, thereby enhancing the manner in which they share and create knowledge.

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AVCI, UMMUHAN, and ESIN ERGUN. "Öğrencilerin Kişilik Özellikleri ve Performanslarına İlişkin Bir SosyalAğ Analizi." KIRŞEHİR EĞİTİM FAKÜLTESİ DERGİSİ 18, no. 3 (2017): 847–64. http://dx.doi.org/10.29299/kefad.2017.18.3.044.

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Rozprawy doktorskie na temat "Social networl analysis"

ATHANASIOU, THOMAS. "Multi-dimensional analysis of social multi-networks : Analysing a 5-layer social network case study." Thesis, Uppsala universitet, Institutionen för informatik och media, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-273908.

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Network theory analysis is applicable to many scientific disciplines (fields) such as biology, statistics and sociology. The social network analysis is one of the various branches of the broader network theory analysis, the social network analysis. It is of high interest among the researchers in social sciences. Social networks have had a significant impact on human civilizations for many centuries. During the last two decades, the main academic interest was addressed towards the research and analysis of a dynamically uprising sector of social networks, the on-line networks, primarily due to the domination of the Internet and technology over human attitudes and relations in modern societies. For many years, research was emphasized on the analysis of simple social networks, whilst during the last decade several researchers started working on the analysis of more complicated social networks, which consist by several smaller social networks. There are important differences between mono and multi-dimensional network analysis. Mono-dimensional analysis provides the research with relevant knowledge. On the other hand, multi-dimensional analysis is still at initial stage. As a result, several potential models related to the multi-networks analysis cannot always provide reliable and adequate outcomes. However, due to the fact that different social networks can be easily combined and form more extended and complicated networks, it is of high importance for the researchers to advance the multi-dimensional analysis and provide more adequate analytical models. The purpose of this thesis is to present the dynamic of the multi-dimensional analysis by consecutively applying both mono and multi-dimensional analysis on a social multi-network. The findings suggest that multi-dimensional analysis can add reliable knowledge on the social network analysis, but many problems that arose due the complexity of the multi-networks structures need to be addressed.

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Junuthula, Ruthwik Reddy. "Modeling, Evaluation and Analysis of Dynamic Networks for Social Network Analysis." University of Toledo / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1544819215833249.

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Vetro, Carla. "La social network analysis nella valutazione delle politiche sociali." Doctoral thesis, Universita degli studi di Salerno, 2012. http://hdl.handle.net/10556/341.

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2009 - 2010 Il tema della valutazione emerge periodicamente nella discussione politica italiana. L’azione del valutare, che rappresenta ormai un’operazione ricorrente nella vita quotidiana, diviene una pratica consolidata anche in seno alle istituzioni pubbliche, indispensabile per costruire un giudizio sul funzionamento delle politiche stesse. La pratica valutativa si rivela, però, difficile da applicare in contesti complessi e dinamici come quelli che caratterizzano gli interventi nel sociale, dove la complessità attiene alla eterogeneità e pluralità di attori coinvolti e alla multiproblematicità dei bisogni territoriali. Quando la riuscita di una politica di intervento dipende non solo dalle capacità di coordinamento dall’alto, cioè di chi programma gli interventi sociali e offre i servizi per rispondere ai bisogni di una comunità, ma anche dalla volontà e dalla partecipazione dal basso, cioè di chi fruisce degli interventi, risulta chiaro quanto un processo di valutazione diventi complesso. In tali situazioni, le tecniche della Social Network Analysis (di seguito analisi delle reti sociali) risultano particolarmente adatte a rilevare, studiare ed interpretare le interazioni di tutti gli attori coinvolti in uno o più interventi di politica sociale. Tali tecniche di analisi vengono utilizzate sempre più spesso nella ricerca valutativa, in quanto si presuppone che ci possa essere una relazione fra le caratteristiche della rete, costituita dagli attori sociali coinvolti nell’attuazione di un programma, e l’efficacia del programma stesso. [a cura dell'autore] IX n.s.

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CURZI, MIRCO. "Content based social network analysis." Doctoral thesis, Università Politecnica delle Marche, 2009. http://hdl.handle.net/11566/242305.

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Moore, John David. "Making Sense of Networks: Exploring How Network Participants Understand and Use Information From Social Network Analysis." Diss., Virginia Tech, 2005. http://hdl.handle.net/10919/103640.

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Many of today's complex public issues are best addressed by multi-sectoral multi-organizational responses that include different types of organizations working together (Kettl, 2008; O'Toole, 1997). Social network analysis (SNA) of interorganizational networks has emerged as a useful tool for network managers to understand the structure and function of the complex networks in which they seek to manage (Human and Provan, 1997, 2000; Provan and Milward, 1995; Provan, Sebastian, and Milward, 1996; Provan, Veazie, Staten, and Teufel-Shone, 2005). The output of an interorganizational SNA typically provides a range of information to network managers including network plots. The network plots provide visual representations of different aspects of the network by showing the kinds of ties between the actors in the network. The information from network analyses can help network managers encourage systems thinking, see the different roles played by organizations, or identify links to outside resources among many other uses, but "will only have practical value to communities if it can be effectively presented, discussed, accepted, and acted on by community leaders and network participants [emphasis added]." (Provan et al., 2005, p. 610). However, little is currently known about if or how the information embedded in network plots is accepted or acted on by network participants. The visual representations of the network (network plots) provided to network participants following a SNA are often open to a range of interpretations that may or may not align with the findings of the analyst or the intended use by network managers, raising many interesting questions. Little is currently known about how differently situated network participants might interpret the same network plots differently. Nor do we understand what factors might influence different individuals or organizations to come up with different interpretations. After conducting a SNA and presenting it to network participants, I conducted interviews with a range of different representatives from participating organizations. I used a particular form of semi-structured interview, a situated micro-element interview from Dervin's Sense Making Methodology (SMM) (Dervin, Foreman-Wernet, and Lauterbach, 2003). I then analyzed the interview transcripts using standard qualitative coding methods (Bailey, 2007) to see if themes emerged that addressed the research questions. I found that most informants had trouble extracting information and meaning from their examination of the plots without that meaning and interpretation being provided by the expert analyst. I posit some potential explanations for why that might be so in the case I studied. I then turn to some interesting methodological considerations that emerged from taking the perspectives of network participants seriously. Finally, I synthesize the subject area and methodological findings into a refined framework for sense-making around network plots and offer propositions and potential approaches for future research. Doctor of Philosophy Many of today's complex public issues are best addressed by multi-sectoral multi-organizational responses that include different types of organizations working together (Kettl, 2008; O'Toole, 1997). Social network analysis (SNA) of interorganizational networks has emerged as a useful tool for network managers to understand the structure and function of the complex networks in which they seek to manage (Human and Provan, 1997, 2000; Provan and Milward, 1995; Provan, Sebastian, and Milward, 1996; Provan, Veazie, Staten, and Teufel-Shone, 2005). The output of an interorganizational SNA typically provides a range of information to network managers including network plots. The network plots provide visual representations of different aspects of the network by showing the kinds of ties between the actors in the network. The information from network analyses can help network managers encourage systems thinking, see the different roles played by organizations, or identify links to outside resources among many other uses, but "will only have practical value to communities if it can be effectively presented, discussed, accepted, and acted on by community leaders and network participants [emphasis added]." (Provan et al., 2005, p. 610). However, little is currently known about if or how the information embedded in network plots is accepted or acted on by network participants. The visual representations of the network (network plots) provided to network participants following a SNA are often open to a range of interpretations that may or may not align with the findings of the analyst or the intended use by network managers, raising many interesting questions. Little is currently known about how differently situated network participants might interpret the same network plots differently. Nor do we understand what factors might influence different individuals or organizations to come up with different interpretations. After conducting a SNA and presenting it to network participants, I conducted interviews with a range of different representatives from participating organizations. I used a particular form of semi-structured interview, a situated micro-element interview from Dervin's Sense Making Methodology (SMM) (Dervin, Foreman-Wernet, and Lauterbach, 2003). I then analyzed the interview transcripts using standard qualitative coding methods (Bailey, 2007) to see if themes emerged that addressed the research questions. I found that most informants had trouble extracting information and meaning from their examination of the plots without that meaning and interpretation being provided by the expert analyst. I posit some potential explanations for why that might be so in the case I studied. I then turn to some interesting methodological considerations that emerged from taking the perspectives of network participants seriously. Finally, I synthesize the subject area and methodological findings into a refined framework for sense-making around network plots and offer propositions and potential approaches for future research.

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Moore, John. "Making Sense of Networks: Exploring How Network Participants Understand and Use Information From Social Network Analysis." Diss., Virginia Tech, 2021. http://hdl.handle.net/10919/103640.

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Magnusson, Jonathan. "Social Network Analysis Utilizing Big Data Technology." Thesis, Uppsala universitet, Avdelningen för datalogi, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-170926.

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As of late there has been an immense increase of data within modern society. This is evident within the field of telecommunications. The amount of mobile data is growing fast. For a telecommunication operator, this provides means of getting more information of specific subscribers. The applications of this are many, such as segmentation for marketing purposes or detection of churners, people about to switching operator. Thus the analysis and information extraction is of great value. An approach of this analysis is that of social network analysis. Utilizing such methods yields ways of finding the importance of each individual subscriber in the network. This thesis aims at investigating the usefulness of social network analysis in telecommunication networks. As these networks can be very large the methods used to study them must scale linearly when the network size increases. Thus, an integral part of the study is to determine which social network analysis algorithms that have this scalability. Moreover, comparisons of software solutions are performed to find product suitable for these specific tasks. Another important part of using social network analysis is to be able to interpret the results. This can be cumbersome without expert knowledge. For that reason, a complete process flow for finding influential subscribers in a telecommunication network has been developed. The flow uses input easily available to the telecommunication operator. In addition to using social network analysis, machine learning is employed to uncover what behavior is associated with influence and pinpointing subscribers behaving accordingly.

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Broccatelli, Chiara. "Going beyond secrecy : methodological advances for two-mode temporal criminal networks with Social Network Analysis." Thesis, University of Manchester, 2017. https://www.research.manchester.ac.uk/portal/en/theses/going-beyond-secrecy-methodological-advances-for-twomode-temporal-criminal-networks-with-social-network-analysis(f0f91f79-7bc3-442c-a16b-e9cf44cc68c3).html.

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This thesis seeks to extend the application of Social Network Analysis (SNA) to temporal graphs, in particular providing new insights for the understanding of covert networks. The analyses undertaken reveal informative features and properties of individuals' affiliations under covertness that also illustrate how both individuals and events influence the network structure. The review of the literature on covert networks provided in the initial two chapters suggests the presence of some ambiguities concerning how authors define structural properties and dynamics of covert networks. Authors sometimes disagree and use their findings to explain opposite views about covert networks. The controversy in the field is used as a starting point in order to justify the methodological application of SNA to understand how individuals involved in criminal and illegal activities interact with each other. I attempt to use a deductive approach, without preconceived notions about covert network characteristics. In particular, I avoid considering covert networks as organisations in themselves or as cohesive groups. I focus on individuals and their linkages constructed from their common participation in illicit events such as secret meetings, bombing attacks and criminal operations. In order to tackle these processes I developed innovative methods for investigating criminals' behaviours over time and their willingness to exchange tacit information. The strategy implies the formulation of a network model in order to represent and incorporate in a graph three types of information: individuals, events, and the temporal dimension of events. The inclusion of the temporal dimension offers the possibility of adopting a more comprehensive theoretical framework for considering individuals and event affiliations. This thesis expands the analysis of bipartite covert networks by adopting several avenues to explore in this perspective. Chapter 3 proposes a different way to represent two-mode networks starting from the use of line-graphs, namely the bi-dynamic line-graph data representation (BDLG), through which it is possible to represent the temporal evolution of individual's trajectories. The following chapter 4 presents some reflections about the idea of cohesion and cohesive subgroups specific to the case of two-mode networks. Based on the affiliation matrices, the analysis of local clustering through bi-cliques offers an attempt to analyse the mechanism of selecting accomplices while taking into account time. Chapter 5 is concerned with the concept of centrality of individuals involved in flows of knowledge exchanges. The theoretical and analytical framework helps in elaborating how individuals share their acquired hands-on experiences with others by attending joint task activities over time. Chapter 6 provides an application of the approaches introduced in the preceding chapters to the specific case of the Noordin Top terrorist network. Here, the knowledge of experience flow centrality measure opens up a new way to quantify the transmission of information and investigate the formation of the criminal capital. Finally, the last Chapter 7 presents some future research extensions by illustrating the versatility of the proposed approaches in order to provide new insights for the understanding of criminals' behaviours.

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Isah, Haruna. "Social Data Mining for Crime Intelligence: Contributions to Social Data Quality Assessment and Prediction Methods." Thesis, University of Bradford, 2017. http://hdl.handle.net/10454/16066.

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With the advancement of the Internet and related technologies, many traditional crimes have made the leap to digital environments. The successes of data mining in a wide variety of disciplines have given birth to crime analysis. Traditional crime analysis is mainly focused on understanding crime patterns, however, it is unsuitable for identifying and monitoring emerging crimes. The true nature of crime remains buried in unstructured content that represents the hidden story behind the data. User feedback leaves valuable traces that can be utilised to measure the quality of various aspects of products or services and can also be used to detect, infer, or predict crimes. Like any application of data mining, the data must be of a high quality standard in order to avoid erroneous conclusions. This thesis presents a methodology and practical experiments towards discovering whether (i) user feedback can be harnessed and processed for crime intelligence, (ii) criminal associations, structures, and roles can be inferred among entities involved in a crime, and (iii) methods and standards can be developed for measuring, predicting, and comparing the quality level of social data instances and samples. It contributes to the theory, design and development of a novel framework for crime intelligence and algorithm for the estimation of social data quality by innovatively adapting the methods of monitoring water contaminants. Several experiments were conducted and the results obtained revealed the significance of this study in mining social data for crime intelligence and in developing social data quality filters and decision support systems.

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Fidalgo, Patrícia Seferlis Pereira. "Learning networks and moodle use in online courses: a social network analysis study." Doctoral thesis, Faculdade de Ciências e Tecnologia, 2012. http://hdl.handle.net/10362/8862.

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Dissertação para obtenção do Grau de Doutor em Ciências da Educação Especialidade em Tecnologias, Redes e Multimédia na Educação e Formação This research presents a case study on the interactions between the participants of the forums of four online undergraduate courses from the perspective of social network analysis (SNA). Due to lack of studies on social networks in online learning environments in higher education in Portugal we have choose a qualitative structural analysis to address this phenomenon. The context of this work was given by the new experiences in distance education (DE) that many institutions have been making. Those experiences are a function of the changes in educational paradigms and due to a wider adoption of Information and Communication Technologies (ICT) from schools as well as to the competitive market. Among the technologies adopted by universities are the Learning Management Systems (LMSs) that allow recording, storing and using large amounts of relational data about their users and that can be accessed through Webtracking. We have used this information to construct matrices that allowed the SNA. In order to deepen knowledge about the four online courses we were studying we have also collect data with questionnaires and interviews and we did a content analysis to the participations in the forums. The three main sources of data collection led us to three types of analysis: SNA, statistical analysis and content analysis. These types of analysis allowed, in turn, a three-dimensional study on the use of the LMS: 1) the relational dimension through the study of forums networks and patterns of interaction among participants in those networks, 2) the dimension relative to the process of teaching and learning through content analysis of the interviews; 3) and finally the dimension related to the participants' perceptions about the use of LMS for educational purposes and as a platform for creating social networks through the analysis of questionnaires.With the results obtained we carried out a comparative study between the four courses and tried to present a reflection on the Online Project of the University as well as possible causes that led to what was observed. We have finished with a proposal of a framework for studying the relational aspects of online learning networks aimed at possible future research in this area.

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Książki na temat "Social networl analysis"

Freeman, Linton. Social Network Analysis. SAGE Publications Ltd, 2008. http://dx.doi.org/10.4135/9781446263464.

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Knoke, David, and Song Yang. Social Network Analysis. SAGE Publications, Inc., 2008. http://dx.doi.org/10.4135/9781412985864.

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Knoke, David. Social network analysis. 2nd ed. Sage Publications, 2008.

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C, Freeman Linton, ed. Social network analysis. SAGE, 2008.

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C, Freeman Linton, ed. Social network analysis. SAGE, 2008.

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Abraham, Ajith, Aboul-Ella Hassanien, and Vaclav Sná¿el, eds. Computational Social Network Analysis. Springer London, 2010. http://dx.doi.org/10.1007/978-1-84882-229-0.

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Pascual-Ferrá, Paola. How to Visualize and Interpret Social Media Networks Using Social Network Analysis Tools. SAGE Publications, Ltd., 2022. http://dx.doi.org/10.4135/9781529610857.

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Missaoui, Rokia, Talel Abdessalem, and Matthieu Latapy, eds. Trends in Social Network Analysis. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-53420-6.

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Reis Pinheiro, Carlos Andre, ed. Social Network Analysis in Telecommunications. John Wiley & Sons, Inc., 2012. http://dx.doi.org/10.1002/9781119200529.

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Pryke, Stephen. Social Network Analysis in Construction. Wiley-Blackwell, 2012. http://dx.doi.org/10.1002/9781118443132.

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Części książek na temat "Social networl analysis"

Whitehead, James, and Mike Peckham. "Social Network Analysis." In Network Leadership. Routledge, 2022. http://dx.doi.org/10.4324/9781003092582-17.

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Medina, Richard, and Nigel Waters. "Social Network Analysis." In Handbook of Regional Science. Springer Berlin Heidelberg, 2019. http://dx.doi.org/10.1007/978-3-642-36203-3_49-1.

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Lee, Viktor. "Social network analysis." In How Firms Can Strategically Influence Open Source Communities. Gabler Verlag, 2012. http://dx.doi.org/10.1007/978-3-8349-7140-1_6.

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Marcus, Sherry E., Melanie Moy, and Thayne Coffman. "Social Network Analysis." In Mining Graph Data. John Wiley & Sons, Inc., 2006. http://dx.doi.org/10.1002/9780470073049.ch17.

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Aggarwal, Charu C. "Social Network Analysis." In Data Mining. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-14142-8_19.

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Mukherjee, S. P., Bikas K. Sinha, and Asis Kumar Chattopadhyay. "Social Network Analysis." In Statistical Methods in Social Science Research. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-2146-7_13.

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Maya-Jariego, Isidro. "Social Network Analysis." In Encyclopedia of Quality of Life and Well-Being Research. Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-94-007-0753-5_2777.

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Serrat, Olivier. "Social Network Analysis." In Knowledge Solutions. Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-0983-9_9.

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Daming, Xu, Wang Xiaomei, and Li Wei. "Social Network Analysis." In The Blackwell Guide to Research Methods in Bilingualism and Multilingualism. Blackwell Publishing Ltd., 2009. http://dx.doi.org/10.1002/9781444301120.ch15.

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Liu, Bing. "Social Network Analysis." In Web Data Mining. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-19460-3_7.

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Streszczenia konferencji na temat "Social networl analysis"

Srivastav, Manoj Kumar, Somsubhra Gupta, and Subhranil Som. "Utilizing Social Network Analysis to Model Social Media Post Popularity with Bayesian Belief Networks." In 2024 International Conference on Big Data Analytics in Bioinformatics (DABCon). IEEE, 2024. https://doi.org/10.1109/dabcon63472.2024.10919420.

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Barbosa, Gabriel, Thaiana Lima, Rodrigo Santos, and Claudia Werner. "Brechó-SocialSECO: Uma Ferramenta para Apoiar Modelagem e Análise de Ecossistemas de Software." In IV Brazilian Workshop on Social Network Analysis and Mining. Sociedade Brasileira de Computação - SBC, 2015. http://dx.doi.org/10.5753/brasnam.2015.6793.

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Em todo sistema de software, existe interação entre componentes. Ao unir uma rede técnica de artefatos com um ambiente social, cria-se uma rede socio-técnica. Visando desenvolver uma ferramenta que modele, analise e incentive as relações sociais na rede socio-técnica, foi proposta a Brechó SocialSECO. Estendeu-se a biblioteca de componente Brechó para melhor entender ecossistemas de software e dar suporte para tomadas de decisão. Este trabalho apresenta a ferramenta e seu funcionamento.

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Maruyama, William Takahiro, and Luciano Antonio Digiampietri. "Co-authorship prediction in academic social network." In Brazilian Workshop on Social Network Analysis and Mining. Sociedade Brasileira de Computação - SBC, 2019. http://dx.doi.org/10.5753/brasnam.2016.6445.

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The prediction of relationships in a social network is a complex and extremely useful task to enhance or maximize collaborations by indicating the most promising partnerships. In academic social networks, prediction of relationships is typically used to try to identify potential partners in the development of a project and/or co-authors for publishing papers. This paper presents an approach to predict coauthorships combining artificial intelligence techniques with the state-of-the-art metrics for link predicting in social networks.

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Melo, Renato Silva, and André Luís Vignatti. "Preprocessing Rules for Target Set Selection in Complex Networks." In Brazilian Workshop on Social Network Analysis and Mining. Sociedade Brasileira de Computação, 2020. http://dx.doi.org/10.5753/brasnam.2020.11167.

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In the Target Set Selection (TSS) problem, we want to find the minimum set of individuals in a network to spread information across the entire network. This problem is NP-hard, so find good strategies to deal with it, even for a particular case, is something of interest. We introduce preprocessing rules that allow reducing the size of the input without losing the optimality of the solution when the input graph is a complex network. Such type of network has a set of topological properties that commonly occurs in graphs that model real systems. We present computational experiments with real-world complex networks and synthetic power law graphs. Our strategies do particularly well on graphs with power law degree distribution, such as several real-world complex networks. Such rules provide a notable reduction in the size of the problem and, consequently, gains in scalability.

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Brandão, Michele A., Matheus A. Diniz, and Mirella M. Moro. "Using Topological Properties to Measure the Strength of Co-authorship Ties." In Brazilian Workshop on Social Network Analysis and Mining. Sociedade Brasileira de Computação - SBC, 2019. http://dx.doi.org/10.5753/brasnam.2016.6455.

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Studying the strength of ties in social networks allows to identify impact at micro-macro levels in the network, to analyze how distinct relationships play different roles, and so on. Indeed, the strength of ties has been investigated in many contexts with different goals. Here, we aim to address the problem of measuring ties strength in co-authorship social networks. Specifically, we present four case studies detailing problems with current metrics and propose a new one. Then, we build a co-authorship social network by using a real digital library and identify how the strength of ties relates to the quality of publication venues when measured by different topological properties. Our results show the best ranked venues have similar patterns of strength of co-authorship ties.

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Bursztyn, Victor S., Marcelo Granja Nunes, and Daniel R. Figueiredo. "How Congressmen Connect: Analyzing Voting and Donation Networks in the Brazilian Congress." In Brazilian Workshop on Social Network Analysis and Mining. Sociedade Brasileira de Computação - SBC, 2019. http://dx.doi.org/10.5753/brasnam.2016.6451.

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The goal of this work is to analyze two of the most central activities in the life of a congressman: raising funds and voting bills. We investigate the Brazilian Congress to shed light on the relationships between the donations received by congressmen elected in 2014 and their voting behaviors during the year of 2015. We merged publicly available data obtained from the Brazilian House of Representatives and the Superior Electoral Court (TSE) in order to create a tripartite network containing campaign donors, elected congressmen, and legal bills. Using this data, we create two projected networks having congressmen as nodes and links given as follows: 1) congressmen who received donations from the same donors (donation network); and 2) congressmen who voted in accordance to each other on legal bills (voting network). After characterizing these networks, we propose three fundamental questions on the behavior of congressmen that could benefit from the methods and concepts provided by Network Science. Finally, we analyze the results and compare them to general domain knowledge.

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Gomes, João Emanoel Ambrósio, and Ricardo Prudêncio. "Educational Social Network Group Profiling: An Analysis of Differentiation-Based Methods." In IV Brazilian Workshop on Social Network Analysis and Mining. Sociedade Brasileira de Computação - SBC, 2015. http://dx.doi.org/10.5753/brasnam.2015.6777.

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Social media communities are usually formed by similarities among users. In educational social networks, several factors propitiate the user group generation, e.g. share the same academic environment or interested in common curricular. In order to explain the group formation resulted from educational social network, we applied two group profiling methods based on differentiation. Wilcoxon rank-sum test and PART rules algorithm were applied to a dataset available, the OJE educational social network. The performed experiments showed that the methods were effective to group profiling generation, characterizing 81.81% and 100% of groups, respectively.

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Soares, Rafael Henrique Santos, Jorge H. C. Fernandes, and Ricardo Sampaio. "Formal Information Flows Among Top Authorities of the Brazilian Federal Government based on Co-word Analysis of Data Published in the Official Gazette." In Brazilian Workshop on Social Network Analysis and Mining. Sociedade Brasileira de Computação - SBC, 2019. http://dx.doi.org/10.5753/brasnam.2016.6450.

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This paper describes a methodology for modeling social networks of formal communications among top authorities of the Brazilian Federal Government grounded on data available in the government official gazette (Diário Oficial da União). The text of a large number of official publications such as presidential decrees, ministerial orders and authority nominations was analyzed for identification of citations to organizations and persons. The co-occurrence of names of persons in such publications created a network of relations among such persons. An ego-network was built around the president Dilma Rousseff. Metrics of social network analysis were collected and analyzed in an exploratory fashion.

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Alcantara, Cássio de, Elaine Ribeiro de Faria Paiva, Maria Camila Nardini Barioni, and Luiz Carlos Oliveira Junior. "Método para Contrastar Percepção de Suporte Social com Dados Extraídos do Twitter em Português." In Brazilian Workshop on Social Network Analysis and Mining. Sociedade Brasileira de Computação - SBC, 2023. http://dx.doi.org/10.5753/brasnam.2023.229750.

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O estudo de características como comportamento, temperamento e suporte social de pessoas pode ser usado para antecipar transtornos psicológicos. Em especial, as redes socias online podem ser usadas como fonte de informação para entender tais características. Os sentimentos presentes nas postagens de um usuário em conjunto com o seu comportamento em uma rede social online podem ser usadas para entender sua percepção de suporte social. Este estudo propõe um método para contrastar o comportamento de um usuário da rede social online Twitter com a sua percepção de suporte social, medida por meio de um questionário. Para isso, primeiramente, foi proposto um modelo não supervisionado para classificação da polaridade das postagens que obteve resultados superiores em todas as três bases testadas quando comparado com os modelos Vader e SentiStrength, atingindo F1 de 57% no melhor caso. Para contrastar os resultados do questionário com o comportamento do usuário no Twitter foram calculados os coeficientes de correlação de Pearson e Ponto-Bisserial, que forneceram informações úteis para entender tal relação, complementando as informações obtidas por meio de questionários.

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Silvestru, Catalin ionut, Marianernut Lupescu, Virgil Ion, and Ramona camelia Silvestru. "CONCEPT: SOCIAL NETWORK EDUCATIONAL PLATFORM." In eLSE 2017. Carol I National Defence University Publishing House, 2017. http://dx.doi.org/10.12753/2066-026x-17-077.

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Due to the growing involvement of social networks in economic, politic and social aspects of people’s lives and taking into account that social networks represent the main ICT means of socializing, having a steady increase of users each year, we the authors consider that social networks can have a positive impact on education, and also, if combined with educational tools, can be used efficiently in a non-formal and informal educational purpose. Thus, this paper sets out to analyse the current use of social networks in educational purposes in order to understand the impact social networks have on education, either positive or negative, and afterwards the authors will create a theoretical model of how a social network for educational purposes should work after analysing the current theoretical functionalities that such a social tool has and comparing them with the theoretical functionalities that an educational platform has. Thus, by analysing the main aspects in regards to how social networks function and how people interact with them, and also doing the same for educational platforms, we the authors will construct a theoretical model that combines the aspects that we consider are necessary for a Social Network Educational Platform to have in order to balance out each negative aspect that both sides have in regards with what user feedback has offered over the last years. The statistical analysis, that will be presented in order to show the importance of social networks in non-formal and informal education and also information on the use of e-learning platforms, will be focused on absolute and relative statistical indicators. The authors believe that the concept used in this current paper can be used as a guideline for further developing more social network educational platforms and tools that take into account Social Media, Social Networks and have a more positive impact on how adults and students see and use ICT for informal and non-formal learning purposes.

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Raporty organizacyjne na temat "Social networl analysis"

Snijders, Tom. Longitudinal Social Network Analysis. Instats Inc., 2024. https://doi.org/10.61700/zimra7qjrsnu11850.

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This three-day workshop provides an introductory overview of longitudinal social network analysis using the RSiena package, focusing on the application of Stochastic Actor-oriented Models to study network dynamics and the co-evolution of networks and behavior. Participants will gain practical skills in modeling network panel data, as well as modeling co-evolution of networks and behavior, for application of these techniques across various academic disciplines.

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Bonnett, Michaela, Chimdi Ezeigwe, Meaghan Kennedy, and Teri Garstka. Using Social Network Analysis to Link Community Health and Network Strength. Orange Sparkle Ball, 2023. http://dx.doi.org/10.61152/scsf6662.

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Social network analysis (SNA) is a technique used to analyze social networks, whether it be composed of people, organizations, physical locations, or objects. It is being increasingly applied across a variety of sectors to gain insight into patterns of behavior and connectivity, the flow of information and behaviors, and to track and predict the effectiveness of interventions or programs. A key area associated with network strength using SNA is the health and wellness of individuals and communities. Both network strength and health and wellness are measured in many ways, which can obfuscate the association, so more consistency and further research is required. Despite this, the existing research using SNA to link characteristics of social networks to health and wellness find that stronger, more connected networks tend to be associated with better health outcomes. These results also present opportunities and insights for effective program implementation in response to disasters, to increase resilience, and to improve outcomes for individuals and communities.

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Johnson, Eric M., and Robert Chew. Social Network Analysis Methods for International Development. RTI Press, 2021. http://dx.doi.org/10.3768/rtipress.2021.rb.0026.2105.

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Social Network Analysis (SNA) is a promising yet underutilized tool in the international development field. SNA entails collecting and analyzing data to characterize and visualize social networks, where nodes represent network members and edges connecting nodes represent relationships or exchanges among them. SNA can help both researchers and practitioners understand the social, political, and economic relational dynamics at the heart of international development programming. It can inform program design, monitoring, and evaluation to answer questions related to where people get information; with whom goods and services are exchanged; who people value, trust, or respect; who has power and influence and who is excluded; and how these dynamics change over time. This brief advances the case for use of SNA in international development, outlines general approaches, and discusses two recently conducted case studies that illustrate its potential. It concludes with recommendations for how to increase SNA use in international development.

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Schmidt, Teresa. Statistical Analysis of Social Network Change. Portland State University Library, 2019. http://dx.doi.org/10.15760/etd.7288.

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Lipsky, Alyson, Molly Adams, and Chinyere Okeke. Ground-Truthing Social Network Analysis for Universal Health Coverage Advocacy Networks in Nigeria. RTI Press, 2024. http://dx.doi.org/10.3768/rtipress.2024.pb.0028.2405.

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Achieving universal health coverage (UHC) requires commitment from a wide range of actors, including policy makers, civil society, and academics. In low- and middle-income countries, creating momentum among stakeholders can be challenging with competing priorities and limited funding. Advocacy coalitions—groups of like-minded organizations coalescing to achieve a common goal—have been used to achieve UHC; however, the effectiveness of advocacy coalitions for UHC is not well understood. This policy brief reviews literature on how social network analysis (SNA)—a method “effective in helping to understand how the stakeholders view one another, share information, cooperate, and take joint action”—has been used in low- and middle-income countries to evaluate UHC advocacy coalitions (Abbot et al., 2022). These findings were validated using experiences from coalition members in Nigeria advocating for UHC. The literature suggests that factors contributing to network success include network cohesion, decentralized network structure, collective action, strong transparency and trust between actors within an advocacy network, and clear communication and collaboration around advocacy objectives and the roles of all involved. The interviews suggest these themes are present in Nigeria as well. Using SNA thinking to conduct interviews in Nigeria, the authors highlighted specific strengths and areas of growth for advocacy coalitions for UHC. La réalisation de la couverture santé universelle (CSU) nécessite l'engagement d'un large éventail d'acteurs, notamment les décideurs politiques, la société civile et les universitaires. Dans les pays à faible et revenu intermédiaire, susciter un élan parmi les parties prenantes peut être difficile avec des priorités concurrentes et un financement limité. Les coalitions de plaidoyer - des groupes d'organisations partageant les mêmes idées se regroupant pour atteindre un objectif commun - ont été utilisées pour réaliser la CSU ; cependant, l'efficacité des coalitions de plaidoyer pour la CSU n'est pas bien comprise. Ce document politique passe en revue la littérature sur la manière dont l'analyse des réseaux sociaux (ARS) - une méthode "efficace pour aider à comprendre comment les parties prenantes se perçoivent mutuellement, partagent des informations, coopèrent et prennent des mesures conjointes" - a été utilisée dans les pays à faible et revenu intermédiaire pour évaluer les coalitions de plaidoyer pour la CSU (Abbot et al., 2022). Ces résultats ont été validés à l'aide des expériences des membres de la coalition au Nigéria plaidant en faveur de la CSU. La littérature suggère que les facteurs contribuant au succès du réseau comprennent la cohésion du réseau, la structure décentralisée du réseau, l'action collective, une transparence et une confiance solides entre les acteurs au sein d'un réseau de plaidoyer, et une collaboration autour des objectifs de plaidoyer et des rôles de tous les intervenants. Les entretiens suggèrent que ces thèmes sont également présents au Nigéria. En utilisant la pensée de l'ARS pour mener des entretiens au Nigéria, les auteurs ont mis en évidence des forces spécifiques et des domaines de croissance pour les coalitions de plaidoyer pour la CSU.

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Shkurov, Yevhen. MEDIA COMMUNICATIONS IN THE SOCIAL DIMENSION OF THE CITY. Ivan Franko National University of Lviv, 2025. https://doi.org/10.30970/vjo.2025.57.13294.

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This article explores the media-communication aspect of the social dimension of the contemporary city, conceptualised as a communication hub within global information networks. The analysis is grounded in the theoretical frameworks of structural functionalism, the network society, and systems communication theory. The study reveals that media not only reflect urban processes but also actively shape urban space, influencing identity, social integration, and public discourse. Keywords: media communications, city, network society, social media, urban space, digitalisation.

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Evans, Daniel, Margaret Moten, Csilla Szabo, and Brian Macdonald. Social Network Analysis in Frontier Capital Markets. Defense Technical Information Center, 2012. http://dx.doi.org/10.21236/ada565112.

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Hoff, Peter D., Adrian E. Raftery, and Mark S. Handcock. Latent Space Approaches to Social Network Analysis. Defense Technical Information Center, 2001. http://dx.doi.org/10.21236/ada458734.

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Xu, Ran. Introduction to Social Network Analysis (Free Seminar). Instats Inc., 2024. https://doi.org/10.61700/zud3mrhp34b2l1910.

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This seminar provides an introduction to social network analysis (SNA), equipping researchers in social sciences, population health science, and systems science with essential tools to examine relationships and behaviors in varied contexts, including mHealth and social media. Attendees will gain a practical understanding of the basics of network theory, data analysis, visualization methods, and real-world applications of SNA.

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Bowman, Elizabeth K., Nkonko Kamwangamalu, Heather Roy, et al. Exploring Social Meaning in Online Bilingual Text through Social Network Analysis. Defense Technical Information Center, 2015. http://dx.doi.org/10.21236/ada622463.

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