Conflict resolution

Linguistics

Philosophy

Biology

Statistics

Theoretical computer science

Information flow

Computer science

Resolution (logic)

Computer network

Genetics

Link (geometry)

Cluster (spacecraft)

Mathematics

Value (mathematics)

Sociology

Artificial intelligence

Mathematical economics

Game theory

Programming language

Community structure

Modularity (biology)

Machine learning

Social science

Journal of Anthropological Research

The paper is devoted to game-theoretic methods for community detection in networks. The traditional methods for detecting community structure are based on selecting denser subgraphs inside the network. Here we propose to use the methods of cooperative game theory that highlight not only the link density but also the mechanisms of cluster formation. Specifically, we suggest two approaches from cooperative game theory: the first approach is based on the Myerson value, whereas the second approach is based on hedonic games. Both approaches allow to detect clusters with various resolution. However, the tuning of the resolution parameter in the hedonic games approach is particularly intuitive. Furthermore, the modularity based approach and its generalizations can be viewed as particular cases of the hedonic games.

An Information Flow Model for Conflict and Fission in Small Groups