Community detection in dynamic social networks a random walk approach
Journal
2011 International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2011
Pages
110-117
Date Issued
2011
Author(s)
Abstract
This study aims to tackling community detection problems in dynamic social networks. The main approach focuses on exploring the idea of random walk in formulating modularity functions for community detection. Under this approach, a modularity function is defined as the difference between the probability of a Markov chain induced by a community and the probability of a null model that assumes no detectable community structure exists in the network. In this paper, we demonstrate the modularity-based approach by applying it to identify group boundaries in an adolescence friendship networks spanning a period of five months. Results and future directions will be discussed.
SDGs
Type
conference paper