A Dynamic Model of Social Network Formation

This chapter considers a dynamic social network model in which agents play repeated games in pairings determined by a stochastically evolving social network. Individual agents begin to interact at random, with the interactions modeled as games. The game payoffs determine which interactions are reinforced, and the network structure emerges as a consequence of the dynamics of the agents’ learning behavior. The chapter studies this in a variety of game-theoretic conditions and show that the behavior is complex and sometimes dissimilar to behavior in the absence of structural dynamics. It argues that modeling network structure as dynamic increases realism without rendering the problem of analysis intractable

Complex network · Dynamic network analysis · Game theory · Mathematical economics · Network dynamics · Network formation · Network structure · Preferential attachment · Social media · Computer Science · Evolutionary Game Theory and Cooperation · Game Theory and Applications · Mathematics · Opinion Dynamics and Social Influence · Psychology · Artificial Intelligence · Theoretical Computer Science