Research practicum 2: Social network analysis

Course goals

After successful completion of the course, the student is able to:

• Define and operationalize network characteristics for ego-networks and complete networks;
• Apply basic data handling- and transformation procedures for social network data using R;
• Formulate specific testable hypotheses related to social networks, both as causes and consequences, based on recent sociological theory;
• Apply appropriate advanced statistical techniques to test such hypotheses with network data.
• Present a social networks study in an oral- or poster format to an academic audience.
• Document research in a replicable way

Content

Social networks are a key concept in numerous sociological theories and empirical applications. Empirically, analyses related to social networks are often quite complex because of interdependencies between actors, which violate the assumptions made in standard statistical methods. In the course, different types of research problems that are central in recent sociological research and that require different statistical approaches will be discussed. We introduce important network characteristics and discuss issues related to the collection and reliability of network data, as well as specific data handling and - transformation procures for network data. We inquire into problems related to how social networks of actors affect their behavior and apply this to multilevel models and other appropriate statistical techniques.  During the whole course, students work on a poster, representing an own research problem, arguments and network analyses. Throughout the course, students will be supplied with recent research articles.