NSF Award
0332075
The goal of this U.S.-Hungarian research project between Jan Tobochnik of Kalamazoo College and George Kampis of Eotvos University, in Budapest, is to study the structure and dynamics of social networks. They will begin with a simple model for the formation and growth of a social network that includes individual nodes with properties or traits that influence how they connect with other nodes. In turn, the researchers will compare their abstract model with empirical data from friendship networks created through surveys of students. The model and survey results will be compared to determine if the probability of forming a connection is proportional to a function of similarity between two nodes. Results should improve the definition of properties of emerging networks, especially the clustering and the hierarchical structure of networks, through observations of certain physical properties such as phase transition from many clusters to a single cluster as a function of control parameters. The effects of removing random nodes and some game-based observations of efficiency measures will be considered as well. Overall, the novel interdisciplinary approach should strengthen current social science work on networks through US-Hungarian expert contributions in systems modeling, mechanisms of cognition, and computational mathematics. Results are expected to improve present methods for examining relationships between real entities such as people, organizations and communities. <br/><br/>This research on evolving complex networks fulfills the program objective of advancing scientific knowledge by enabling experts in the United States and Central Europe to combine complementary talents and share research resources in areas of strong mutual interest and competence. Broader impacts also include the introduction of U.S. students to interdisciplinary science and to the international research community through work at Hungarian institutions and direct involvement with the project's central network survey.
