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Analysing the simultaneous dynamics of social networks and individual behavior Tom A.B. Snijders ICS University of Groningen http://stat.gamma.rug.nl/snijders/ A natural way to think of social and economic interaction structure is in terms of social networks. Studies of social networks have focused traditionally on the role of networks as opportunities and constraints for the behavior and performance of the actors. The behavior and performance of individual persons and other social actors (e.g., firms, organizations) is conditioned to an important extent by their embeddedness in social ties with other actors. But there is also an influence into the other direction: social networks arise as the outcome of individual choices and behavior. The selection of others as interaction partners depends strongly on characteristics (such as perceived abilities and attitudes) and behavior of the actors involved, as well as on the earlier or present network structure and the embeddedness in the wider social network. The study of the influence of social networks on behavior and performance on one hand, and the influence of behavior and performance on relation structure on the other hand, is complicated because this mutual influence is hard to disentangle. In many fields of study, there is much uncertainty and discussion about the extent to which on one hand relational structure determines individual behavior, performance, and attitudes, and the extent to which on the other hand behavior, performance, and attitudes determine relational structure. Examples are the association between friendship and criminal behavior, between friendship and smoking, between interpersonal influence and social norms, between inter-firm relations and the adoption of new technology. Recently, statistical methods have been developed that can be used to analyze the dynamics of social networks, given that repeated observations are available of the social network of a given group of actors (see Snijders, 2001). These are based on stochastic microsimulation models representing the dynamics of a relational network in a set of actors. Associated to these models are procedures for parameter estimation and testing, using Markov chain Monte Carlo methods. Extensions of these methods will be presented where the dynamics of the social network is coupled to the dynamics of the behavior of the actors in the network. This involves a micro-simulation model that expresses the formation and dissolution of network ties together with the dynamics of individual characteristics. An example is presented which illustrates the two-way influence between friendship relations and smoking behavior of adolescents. Reference Snijders, Tom A.B. (2001). The Statistical Evaluation of Social Network Dynamics. Pp. 361-395 in Sociological Methodology -2001, edited by M.E. Sobel and M.P. Becker. Boston and London: Basil Blackwell. Brief curriculum vitae of Tom A. B. Snijders (July 2003) Address Dept. of Sociology University of Groningen Grote Rozenstraat 31 9712 TG Groningen The Netherlands Email web-page [email protected] http://stat.gamma.rug.nl/snijders/ Birth September 26, 1949 in Tilburg (The Netherlands) Academic Degrees June 1973 May 4, 1979 M.Sc. in Mathematics, specializing in Mathematical Statistics, University of Groningen (cum laude awarded). Ph.D. in Mathematics, specializing in Mathematical Statistics, University of Groningen (cum laude awarded). Ph.D. Thesis Asymptotic optimality theory for testing problems with restricted alternatives. Ph.D. supervisor prof.dr. W. Schaafsma. Present position Professor of Methodology and Statistics at the Dept. of Sociology (Faculty of Social and Behavioral Sciences), University of Groningen. Scientific Director of the ICS (Interuniversity Center for Social Science Theory and Methodology), a research and graduate school that is a cooperative activity of the departments of sociology of the Universities of Groningen, Utrecht, and Nijmegen. Main research interests Statistical modeling in the social sciences, with special interest in social network analysis and multilevel modeling, and in statistical models reflecting substantive theory. Also: mathematical sociology; item response theory. Some current functions and memberships Member of the International Statistical Institute. Associate Editor, Journal of Educational and Behavioral Statistics. Associate Editor, Psychometrika. Associate Editor, Journal of Social Structure.