Browsing by Subject "social network analysis"

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  • Reyes-García, Victoria; Andrés-Conejero, Oriol; Fernandez-Llamazares Onrubia, Alvaro; Diaz-Reviriego, Isabel; Molina, José Luis (2019)
    Society's understanding of a conflict is mediated by information provided in mass media, for which researchers stress the importance of analyzing media portrays of stakeholders in a conflict. We analyze information from the Bolivian press regarding the construction of a road crossing the Isiboro-Secure Indigenous Territory and National Park (TIPNIS). Using stakeholder's and social network analyses, we explore stakeholder's positions and alliances as represented in the media and contrast it with previous scholarly work. We found that some actors cited as central in scholar analyses of the conflict are largely absent in the media (e.g., private investors, conservationist sector) and that the media tend to present stakeholders as having more homogeneous positions than the academic literature does while also neglecting some important alliances in their account. The media also suggests that Indigenous communities are forging stronger alliances with urban sectors and civil society, alliances not stressed by researchers.
  • Haq, Ehsan ul; Braud, Tristan; Kwon, Young D.; Hui, Pan (2020)
    Computational Politics is the study of computational methods to analyze and moderate users' behaviors related to political activities such as election campaign persuasion, political affiliation, and opinion mining. With the rapid development and ease of access to the Internet, Information Communication Technologies (ICT) have given rise to massive numbers of users joining online communities and the digitization of political practices such as debates. These communities and digitized data contain both explicit and latent information about users and their behaviors related to politics and social movements. For researchers, it is essential to utilize data from these sources to develop and design systems that not only provide solutions to computational politics but also help other businesses, such as marketers, to increase users' participation and interactions. In this survey, we attempt to categorize main areas in computational politics and summarize the prominent studies in one place to better understand computational politics across different and multidimensional platforms. e.g., online social networks, online forums, and political debates. We then conclude this study by highlighting future research directions, opportunities, and challenges.
  • Rimpela, Arja; Kinnunen, Jaana M.; Lindfors, Pirjo; Soto, Victoria Eugenia; Salmela-Aro, Katariina; Perelman, Julian; Federico, Bruno; Lorant, Vincent (2020)
    Peer networks at school and students' position in these networks can influence their academic well-being. We study here individual students' network position (isolation, popularity, social activity) and peer network structures at the school level (centralization, density, clustering, school connectedness) and their relations to students' academic well-being (school burnout, SB; schoolwork engagement, SE). Classroom surveys for 14-16-year-olds (N = 11,015) were conducted in six European cities (SILNE survey). Students were asked to nominate up to five schoolmates with whom they preferred to do schoolwork. SB and SE correlated negatively (-0.32; p <0.0001). Students had on average 3.4 incoming (popularity; range 0-5) and 3.4 outgoing (social activity; 0-5) social ties. Percentage of isolated students was 1.4. Students' network position was associated weakly with academic well-being-popular students had less SB and higher SE, and socially active students had higher SE. School-level peer networks showed high clustering and school connectedness, but low density and low centralization. Clustering was associated with higher SB. Low centralization and high school connectedness protected from SB. Dense networks supported SE as did high average school connectedness. Correlations between these network indicators and academic well-being were, however, low. Our study showed that both students' network position and network characteristics at the school level can influence adolescents' academic well-being.
  • Korhonen, Jaana; Giurca, Alexandru; Brockhaus, Maria; Toppinen, Anne (2018)
    To foster innovativeness for supporting (forest-based) bioeconomy development, participation in decision-making and interaction between diverse actors become a necessary precondition for designing and implementing transition policies. However, who forms the emerging policy networks, and which policy beliefs are promoted? Based on data from a national online survey, we performed a quantitative social network analysis to investigate emerging social structures and policy beliefs in the context of the Finnish forest-based bioeconomy. Our explorative analysis shows that research, governmental, and industrial organizations mainly constitute the Finnish forest-based bioeconomy network. Actors primarily exchange information, and most key organizations report high levels of trust among each other. However, the network structure is rather closed. This raises concerns about equal benefit sharing and the inclusiveness of concerned actors. We discuss the implication of this network structure for enabling new innovations. Finally, we present the key aspects and drivers of business as usual, and suggest an option for or a more transformative change in the Finnish forest-based bioeconomy.
  • Shin, Bokyong; Rask, Mikko (2021)
    Online deliberation research has recently developed automated indicators to assess the deliberative quality of much user-generated online data. While most previous studies have developed indicators based on content analysis and network analysis, time-series data and associated methods have been studied less thoroughly. This article contributes to the literature by proposing indicators based on a combination of network analysis and time-series analysis, arguing that it will help monitor how online deliberation evolves. Based on Habermasian deliberative criteria, we develop six throughput indicators and demonstrate their applications in the OmaStadi participatory budgeting project in Helsinki, Finland. The study results show that these indicators consist of intuitive figures and visualizations that will facilitate collective intelligence on ongoing processes and ways to solve problems promptly.
  • Shin, Bokyong (2021)
    Although social capital is a relational concept, existing studies have focused less on measuring social relations. This article fills the gap by reviewing recent studies that used network measures grouped into three types according to the measurement level. The first group defined social capital as an individual asset and used node-level measures to explain personal benefits. The second group defined social capital as a collective asset and used graph-level measures to describe collective properties. The third group used subgraph-level measures to explain the development of social capital. This article offers a link between the concepts and measures of social capital.
  • Hill, Mark J.; Vaara, Ville; Säily, Tanja; Lahti, Leo; Tolonen, Mikko (CEUR-WS.org, 2019)
    CEUR Workshop Proceedings
  • Toikkanen, Tarmo (Helsingfors universitet, 2005)
    As computer technology evolves, both the need for knowledge workers and the pressure to increase the effectiveness of teaching with the help of ICT increase. Teaching of the skills needed by the knowledge workers requires new pedagogy, where instead facts and obedience the focus is on skills, independence and learning to learn. The use of ICT in education brings its own challenges to learning situations. Social constructivist computer supported collaborative learning (CSCL) is becoming a major challenger for the traditional teacher-centered learning. One of these methodologies is Progressive Inquiry, which is developed in Finland. Since the social constructive theory emphasizes the relations between learners more than the individuals' actions, research in this field must also take into account the interactions that occur in learning situations. While traditional psychological and pedagogical methods are not applicable, an old method of social sciences, SNA or social network analysis is designed specifically for the analysis of groups of people. Applications of SNA in psychology and collaborative learning are however few and preliminary, and no reliable evidence on the applicability nor useful results exist. The purpose of this study is to find out if SNA can be applied to this field of research. In this study SNA was used to analyze the learning situations of 23 classes in comprehensive and secondary schools that used Progressive inquiry. The results show that SNA can be applied to the study of CSCL, since the analysis produced preliminary measurements that were related to the quality of the course. The results are also in concordance with social constructivist theory: a course's usefulness increases as the several students write high quality messages and participate widely in different conversations.