Social Network Analysis
- Understanding basic concepts of social network analysis, Understanding how networks can contribute to the explanation of specific social, political, economic and cultural phenomena, Mastering basic skills of working with SNA software Gephi, Pajek, R packages, Acquaintance with biblographic network analysis software VosViewer, CitNetExplorer
- Able to independently master new research methods, change the scientific and production profile of their activity.
- Able to retrieve data from open statistical databases, archives, and other public sources.
- Able to evaluate and revise learned scientific methods and methods of activity.
- Network terminology and metrics. Describing, visualising and analysing networks. Software: Pajek, Gephi, R.1) Network terminology and basic concepts Definition of a network. Nodes (vertices) and links (arcs, edges). Directed and undirected relations. Representation of social relations as graphs. How to record network data: adjacency matrix, edge list, node list. 2) Network structure: centrality Egonetworks, k-neighbors. Centrality measures: in/out degree centrality; betweenness; closeness; eigenvector, Katz & PageRank. Centrality vs. centralization. Degree distribution and centralization measures. 3) Social capital What is social capital? Definitions of P.Bourdieu, J.S.Coleman, R.D.Putnam, A.Portes. Bonding and bridging; social capital formation; social capital and economic development. World Bank's programs with emphasis on social capital. Operationalization and measures of social capital. 4) Network structure: components and communities. Weak, strong, and giant components. Diffusion of information in networks. Real life examples. Network modularity. Community detection algorithms: local and global definitions, vertex dissimilarity. Clustering: hierarchical, partitional, spectral. Communities in real-life networks.
- Network in bibliometrics: using SNA for bibliographic search and analysis. Software: VosViewer and CitNetExplorer5) Networks in bibliometrics. Two-mode (bimodal) networks. Affiliation matrix. Weighted networks. Bibliometric networks: co-citation, bib-coupling, co-authorship. Journal networks. Timeline in bibliometric analysis.
- Network theory and applications. Network models. Software: Pajek, Gephi, R6) Network models: Random graphs (Erdos-Renuy), Small world, Preferential attachment (Power law). Network characteristics: shortest path, clusterization coefficient, degree distribution. 7) Diffusion of information in networks. Opinion formation. Social movements. Recruiting through networks. 8) Project presentations 9) Test
- Individual project (written essay) with oral presentation
- In-class Participation
- Interim assessment (4 module)0.4 * In-class Participation + 0.35 * Individual project (written essay) with oral presentation + 0.25 * Test
- Scott, J. (DE-588)132315661, (DE-576)299070239. (2009). Social network analysis : a handbook / John Scott. Los Angeles [u.a.]: Sage. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edswao&AN=edswao.307646734
- Kadry, S., & Al-Taie, M. Z. (2014). Social Network Analysis : An Introduction with an Extensive Implementation to a Large-scale Online Network Using Pajek. Bentham Science Publishers.