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Group formation is important in many economic contexts. The current literature on group formation assumes that individuals may join any existing group. In this paper, I consider the implications of social, geographic, and informational constraints to group membership decisions. I embed the players in a network of relationships, which constrains their choice of groups--they may only join a group if that group contains a member that they are connected to on the network. I then examine how this network constraint affects the equilibrium group structure. I show that even with complete information, unconstrained individuals form groups that are inefficiently large. When individuals are constrained, the resulting group structures are much closer to the socially optimal group structure, because the constraint limits the ability of the individual to free ride on the efforts of other group members. The efficiency of the outcome is related to the structure of the network constraint--outcomes are more efficient when networks are sparse and have few random connections.
Social groups are fundamental building blocks of human societies. While our social interactions have always been constrained by geography, it has been impossible, due to practical difficulties, to evaluate the nature of this restriction on social gro
The spontaneous formation and subsequent growth, dissolution, merger and competition of social groups bears similarities to physical phase transitions in metastable finite systems. We examine three different scenarios, percolation, spinodal decomposi
Successfully integrating newcomers into native communities has become a key issue for policy makers, as the growing number of migrants has brought cultural diversity, new skills, and at times, societal tensions to receiving countries. We develop an a
Quantifying human group dynamics represents a unique challenge. Unlike animals and other biological systems, humans form groups in both real (offline) and virtual (online) spaces -- from potentially dangerous street gangs populated mostly by disaffec
Community structure is an important property of complex networks. An automatic discovery of such structure is a fundamental task in many disciplines, including sociology, biology, engineering, and computer science. Recently, several community discove