A bottom-up method for constructing topic hierarchies

Yuhao Zhang, Wenji Mao, Xiaochen Li

Abstract: In security-related applications, it is of great need to construct topic hierarchies from the data automatically. It can help us better understand the contents and structure of information and benefit many applications in security informatics. The existing topic hierarchy construction methods either need to specify the structure manually, or are not robust enough for sparse social media data such as microblog. In this paper, we propose an approach to automatically construct topic hierarchies from microblog data in a bottom up manner. We first detect the fine grained topics and then build the topic structure based on a multi-branch hierarchical construction method. We conduct a preliminary empirical study based on Weibo data. The experimental results show that the hierarchical topic structure generated by our method can provide meaningful results.

External IDs:dblp:conf/isi/ZhangML15