Social Network Analysis
- abilities (a) to apply methods of social network analysis to sociological data and (b) develop research design within social network analysis framework
- Basic concepts of social network analysisNodes. Edges. Matrix. Graph. Observable and perceptive networks. Macro, meso- and micro-levels of analysis. Types of network data. Full network data & ego-network data. Network boundary: realist and nominalist approaches. Sampling in network analysis. Attributes. Measuring links. Sources of network data.
- Centrality & centralizationCentrality & centralization. In-degree & out-degree. Farness and closeness. Node betweenness & edge betweenness. Eigenvector centrality. Bonacich power.
- CohesionCohesion in networks. Density. Geodesic distance. Diameter. Reciprocity and transitivity. Node’s attributes, groups & homophily. Group’s external and internal ties. Assortativity.
- Ego-networks & structural holesDefining ego-network. Ego-networks size and density. Redundancy, effective size and efficiency. Inefficiency as a function of size, density, hierarchy & structural equivalency. Structural holes and constraint.
- Community structureTop-down and bottom-up approaches to community structure. Cliques, n-cliques, clique percolation ect. Componets. Fractions. Modularity maximization. Goodness of fit measures.
- Equivalent positions & block-modellingPositions and roles in network analysis. Equivalent positions. Structural and regular equivalency. Blocks. Block-matrix and image-matrix. Goodness of fit. Coalition, hierarchy, community structure & isolation.
- Multiplex & two-mode networksMatrix operations. Two-mode to one-mode. Projection. Two-mode centralities, density, community structure.
- Statistics & modelling in SNAMonadic, dyadic and mixed hypothesis.
- Seminar1 gradehome reading presentations during classes & class discussions
- Seminar2 gradeseminar project presentations
- Final examform of a written research report discussing network measures & their interpretations
- Interim assessment (4 module)0.22 * Discussion + 0.2 * Final exam + 0.29 * Seminar1 grade + 0.29 * Seminar2 grade
- Luke, D. A. (2015). A User’s Guide to Network Analysis in R. Cham: Springer. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1114415
- Etaner-Uyar, A. S., & Gündüz-Ögüdücü, S. (2014). Social Networks: Analysis and Case Studies. Wien: Springer. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=812923