Coherent Topic Hierarchy: A Strategy for Topic Evolutionary Analysis on Microblog Feeds

Topic evolutionary analysis on microblog feeds can help reveal users’ interests and public concerns in a global perspective. However, it is not easy to capture the evolutionary patterns since the semantic coherence is usually difficult to be expressed and the timeline structure is always intractable to be organized. In this paper, we propose a novel strategy, in which a coherent topic hierarchy is designed to deal with these challenges. First, we incorporate the sparse biterm topic model to extract some coherent topics from microblog feeds. Then the topology of these topics is constructed by the basic Bayesian rose tree combined with topic similarity. Finally, we devise a cross-tree random walk with restart model to bond each pair of sequential trees into a timeline hierarchy. Experimental results on microblog datasets demonstrate that the coherent topic hierarchy is capable of providing meaningful topic interpretations, achieving high clustering performance, as well as presenting motivated patterns for topic evolutionary analysis.