Dynamic community in online social networks

被引：0
作者：
Wang, Li [1 ,2 ]
Cheng, Xue-Qi [2 ]
机构：
[1] College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan
[2] Institute of Computing Technology, Chinese Academy of Sciences, Beijing
来源：
Jisuanji Xuebao/Chinese Journal of Computers | 2015年 / 38卷 / 02期
基金：
中国国家自然科学基金;
关键词：
Abnormal swarm detection; Community evolution; Dynamic community detection; Online social networks; Social computing; Statistical inference;
D O I：
10.3724/SP.J.1016.2015.00219
中图分类号：
学科分类号：
摘要：
It is an important issue in online social networks to detect hidden communities and track their evolution process, which will help understanding the latent topology, predicting its evolution trend, discovering abnormal events and controlling the network. We firstly give the explanation of the relationship between community detection research and community evolution research, and put forward their main challenges. Then we introduce the related research from two different angles, one is dynamic community in homogenous social networks and the other is that in heterogeneous social networks. To clearly state the first area, we introduce the related work by dividing them into 4 classes on the evaluation mechanism: temporal-spatial independent evaluation based, temporal-spatial integrated evaluation based, unified evaluation based and incremental algorithms. An important application is also reviewed that is detection abnormal swarm events. At last some future research topics are given. ©, 2015, Science Press. All right reserved.
引用
收藏
页码：219 / 237
页数：18
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