30389 - SOCIAL NETWORK ANALYSIS (Introduction to Network Science)
CLEAM - CLEF - CLEACC - BESS-CLES - WBB - BIEF - BIEM - BIG
Course taught in English
Go to class group/s: 31
Introduction to network science; Network structures: understanding social networks; Using graphs to represent social relations; Creating network data; Visualizing networks; Using matrices to represent social relations; Working with network data.
Network characteristics: Connection; Embedding; Ego networks; Centrality and power; Cliques and sub-groups; Positions and roles: The idea of equivalence; Multiplexity; Two-mode networks; Big networks; Small world networks; Scale free networks. Network origins; Network consequences; Network processes: Contagion; Diffusion; Influence; Network dynamics.
Applications of Social Network Analysis: intra-organizational communities and firms; strategic alliances and mergers & acquisitions.
- Class contribution (exercises, class discussion, and, of course, attendance and punctuality): 40%.
- Final written exam (test on the use of network concepts, data, and their applications): 60%.
- Final written exam (test on the use of network concepts, data, and their applications): 100%.
- S. WASSERMAN, K. FAUST, Social network analysis: Methods and applications (Vol. 8), Cambridge University Press.
- R.A. HANNEMAN, M. RIDDLE, Introduction to social network methods, available on line at http://faculty.ucr.edu/~hanneman/nettext/
- G. SODA (editor), Introduction to Network Science, Il Pellicano, EGEA, 2014.
The teaching method requires the use of personal computers for the lab-sessions. The completion of exercises is an important aspect of the class, and help to familiarize with the UCINET software that includes the standard tools used in organizational network analysis.
All students are required to download on their PC the latest version of UCINET (www.analytictech.com).