A Novel Approach for Detecting Relationships in Social Networks Using Cellular Automata Based Graph Coloring

All the social networks can be modeled as a graph, where each roles as vertex and each relationroles as an edge. The graph can be show as G = [V;E], where V is the set of vertices and E is theset of edges. All social networks can be segmented to K groups, where there are members in eachgroup with same features. In each group each person knows other individuals and is in touch withthem. In this study, the main goal is introducing a new approach for detecting these groups andminimizing the number of these groups using a cellular automat algorithm. There are two types ofsocial networks, containing simulated social network and real social network. The results show thatthe introduced method has a great potential to signicantly reduce the number of colors assignedand running time of the program.