Community evolution in dynamic social networks
- 10.2991/iccia.2012.5How to use a DOI?
- social network, community recognition, time step, connectitvity graph
This paper proposed a framework and an algorithm for identifying communities in dynamic social networks. In order to handle the drawbacks of traditional approaches for social network analysis, we utilize the community similarities and infrequent change of community members combined with community structure optimization to develop a Group-based social community identification model to analyze the change of social interaction network with multiple time steps. According to this model ,we introduced a greed-cut algorithm and depth-search-first approach and combine them to develop a new algorithm for dynamic social interaction network recognition (called ADSIN). In addition, we conduct experiments on the dataset of Southern Women, the experiment results validate the accuracy and effectiveness of ADSIN.
- © 2013, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Gang Wang AU - Yuli Lei AU - Chongjun Wang AU - Shaojie Qiao PY - 2014/05 DA - 2014/05 TI - Community evolution in dynamic social networks BT - Proceedings of the 2012 2nd International Conference on Computer and Information Application (ICCIA 2012) PB - Atlantis Press SP - 21 EP - 24 SN - 1951-6851 UR - https://doi.org/10.2991/iccia.2012.5 DO - 10.2991/iccia.2012.5 ID - Wang2014/05 ER -