Publications

A dynamic model for social networks

Field, Richard V.; Link, Hamilton E.; Skryzalin, Jacek S.; Wendt, Jeremy D.

Social network graph models are data structures representing entities (often people, corpora- tions, or accounts) as "vertices" and their interactions as "edges" between pairs of vertices. These graphs are most often total-graph models -- the overall structure of edges and vertices in a bidirectional or directional graph are described in global terms and the network is gen- erated algorithmically. We are interested in "egocentrie or "agent-based" models of social networks where the behavior of the individual participants are described and the graph itself is an emergent phenomenon. Our hope is that such graph models will allow us to ultimately reason from observations back to estimated properties of the individuals and populations, and result in not only more accurate algorithms for link prediction and friend recommen- dation, but also a more intuitive understanding of human behavior in such systems than is revealed by previous approaches. This report documents our preliminary work in this area; we describe several past graph models, two egocentric models of our own design, and our thoughts about the future direction of this research.