An approach to mining social networks in chat room

作者：Huang, Faliang^*; Xiao, Nanfeng; Cheng, Xinguo; Xiao, Ruliang

来源：Journal of Computational Information Systems, 2011, 7(1): 135-143.

• Chat rooms
• Content analysis
• Content similarity
• Semantic similarity
• Social Networks
• Thread structure association
• Vector space models

Mining social networks in a chat room is valuable since it makes it possible to discover essential relations among chatters in chat rooms and effectively monitor the chat rooms. In existing works, some focus on message content analysis, some put emphasis on the underlying thread structure in the chatter dialogs, but few works are reported on approaches to mining social networks in a chat room. In this paper, we propose a novel mining approach which discovers social networks by integrating dialog thread structure association with message content similarity. We improve traditional vector space model (VSM) with semantic similarity of terms, make some refinements on the old heuristics in PieSpy and give novel rules resulted from large amount of observation. We experimentally evaluate the proposed approach and demonstrate that our algorithm is promising and efficient.

• 出版日期2011-1
• 单位华南理工大学