Quantitative Methods in the
Social Sciences 2

Social interactions and social networks

Events

The study of social interactions, or social networks, is central to understanding the dynamics of the relations between social actors, as well as their behaviour and performance. Social actor as used here can refer to individuals, companies, associations, countries, etc. Basic to the study of social networks is the insight that a dyadic focus is not enough for understanding social interactions, but indirect ties, third party-effects, and other more complex patterns of ties between multiple actors have profound consequences for their behaviour. Furthermore, interactions between social actors lead to feedback patterns and phenomena that can be studied only longitudinally. Some examples of such patterns are peer relations between adolescents and the interrelation between peer networks and developments of lifestyle behaviour, social or antisocial behaviour, various health-related practices, etc.; cooperation and competition between employees in a work setting; ethnic relations and attitudes of individuals with respect to religious and ethnic groups; and strategic alliances between companies. The feedback patterns between interactions and attitudes or behaviour can in some cases lead to fast occurring changes in aggregate opinions, polarization, etc. The relevance of these topics to Europe is evident.

The focus on ties between actors distinguishes the methodology of social network analysis from other methodologies in the social sciences, both with respect to data collection, construction and measurement of variables, and data analysis. The standard assumption of independent cases is not adequate here. In the past years, important advances have been made, and are still being made, in the methodology of social network analysis. Computers play a central and multi-faceted role here: computer communication has revolutionary impacts on social interactions (chatting, computer-mediated friendships, discussion groups, email); the world-wide web has led to many new possibilities for data collection and has itself become an object of investigation; and computer-intensive analysis methods enable simulation-based studies of social networks that would earlier have been unthinkable. Moreover, there has been a growing and fruitful collaboration between substantive social scientists and methodologists/statisticians in the study of social networks.

Core members

Leaders
Anuška Ferligoj, University of Ljubljana

Tom Snijders, University of Oxford and University of Groningen

Members
Vladimir Batagelj, University of Ljubljana

Antonio Chiesi, University of Milano Statale

Blazenka Divjak, University of Zagreb

Wouter de Nooy, University of Amsterdam

Christofer Edling, Jacobs University Bremen

Emmanuel Lazega, University of Paris Dauphine

Diane Payne, University College Dublin

Gregor Petrič , University of Ljubljana

Beate Völker, University of Utrecht

Rafael Wittek, University of Groningen