Clearing the fog: Fuzzy, overlapping groups for social networks
| Venue: | Social Networks |
| Citations: | 8 - 1 self |
BibTeX
@ARTICLE{Davis_clearingthe,
author = {George B. Davis and Kathleen M. Carley},
title = {Clearing the fog: Fuzzy, overlapping groups for social networks},
journal = {Social Networks},
year = {},
pages = {2008}
}
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Abstract
Abstract: Humans are well known to belong to many associative groups simultaneously, with various levels of affiliation. However, most group detection algorithms for social networks impose a strict partitioning on nodes, forcing entities to belong to a single group. Link analysis research has produced several methods which detect multiple memberships but force equal membership. This paper extends these approaches by introducing the FOG framework, a stochastic model and group detection algorithm for fuzzy, overlapping groups. We apply our algorithm to both link data and network data, where we use a random walk approach to generate rich links from networks. The results demonstrate that not only can fuzzy groups be located, but also that the strength of membership in a group and the fraction of individuals with exclusive membership are highly informative of emerging group dynamics.
