BBS Hot Topic Tracking Based on Theme Evolution Graph
Rongbo Wang · Information Sciences · 2013
Internet public hot topics detecting and tracking has become a ?ourishing frontier in the Web mining community and has a wide range of application prospects.This paper studies BBS hot topics tracking using theme evolution graph.Firstly,we create an algorithm to automatically detect the hot topics of BBS threads based on co-word analysis and bisecting K-means algorithm.Then,the calculation methods of attention-degree for hot topic and semantic distance between hot topics are presented.Finally,a approach for BBS hot topics tracking based on theme evolution graph is proposed.Experimental results on thousands of real BBS threads demonstrate that the approach proposed in this paper is effective.