This course offers an introduction to fundamental concepts, methods, and applications of social network analysis (SNA) on the basis of selected empirical studies and computer exercises.
Objective
After this course students will be (1) familiar with the relational paradigm, (2) capable of performing basic statistical analysis of social networks with R, and (3) able to assess strengths and weaknesses of the network approach in the social sciences.
Content
Social network analysis deals with the question of how social actors (people or organizations) are tied together by one or several specific types of interdependency, what patterns and structures emerge from their interactions, and how these structures can be explained by social processes and mechanisms. The course starts with a compilation of graph-theoretic foundations and basic concepts. In the remainder of the semester we cover a new topic in each session such as centrality, brokerage, small worlds, scale free networks, homophily, and diffusion. Students are expected to actively participate in the seminar, to give either a short presentation on a scientific article during the semester or to conduct their own small research project. Additionally, a short essay on one of the covered topics is required.
Literature
Scott, J. 2000. Social Network Analysis. A Handbook. 2nd Edition. Newbury Park, Ca: Sage.
De Nooy, W., Mrvar, A. und V. Batagelj. 2005. Exploratory Social Network Analysis with Pajek. Cambridge: Cambridge University Press.
Degenne, A. and M. Forsé. 1999. Introducing Social Networks. London: Sage.
Wasserman, S. und K. Faust (1994): Social Network Analysis. Methods and Applications. Cambridge: Cambridge University Press.
Performance assessment
Performance assessment information (valid until the course unit is held again)