300099 Inequalities in Social Networks (S) (WiSe 2014/2015)

Social network analysis is used to investigate the relationships and interactions among actors, such as individuals, organizations, institutions or states. According to the network perspective, patterns of relationships among actors have manifold influences and consequences not only for the actors themselves but also for society at large. In particular, the structure and dynamics of the relations in which individuals are embedded have been consistently shown to be crucial for the production and persistence of different forms of inequality. Some questions which arise in the intersection between networks and social inequality include the following: Who gets the job? Who gets promoted? Who is happy or depressed? Who commits a crime? Which children achieve higher grades? Who gets divorced? Who gets a sexually-transmitted disease?

The aim of this course is to introduce students to network analysis through empirical studies, theories and models by focusing on its use in social sciences and inequality studies. The seminar is not only about reviewing empirical studies, for example, about job referrals and hiring, obesity and depression, crime and terrorism, marriage and divorce, scientific publications and citations, school achievement, social contagion and innovation, or romantic relationships and sexually-transmitted diseases; but also investigating patterns, similarities, and differences in the social networks surrounding these and other related phenomena relevant to inequalities. Are there any regularities in the way individual characteristics and preferences affect the formation, stability and dissolution of social ties? Are individual outcomes similarly constrained or enhanced by the position individuals occupy inside a network? Are they equally affected by the structure of the network? To answer these questions, empirical research, theories and models will be selectively combined and discussed in each session.

The course also has a practical part. During the practical part, students will acquire skills which will enable them to utilize network analysis in their empirical projects. The students will have an opportunity to learn about data collection methods and analysis techniques using data visualization software such as Gephi in combination with standard statistical packages such as STATA.