Constructing Topic Hierarchies from Social Media Data

Yuhao Zhang, Wenji Mao, Dajun Zeng

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Constructing topic hierarchies from the dataautomatically can help us better understand the contents andstructure of information and benefit many applications insecurity informatics. The existing topic hierarchy constructionmethods either need to specify the structure manually, or arenot robust enough for sparse and noisy social media data suchas microblog. In this paper, we propose an approach toautomatically construct topic hierarchies from microblog datain a bottom up manner. We detect topics first and then build thetopic structure based on a tree combination method. Weconduct a preliminary empirical study based on the Weibo data. The experimental results show that the topic hierarchiesgenerated by our method provide meaningful results.

Original languageEnglish (US)
Title of host publicationProceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages4
ISBN (Electronic)9781467384926
StatePublished - Jan 29 2016
Externally publishedYes
Event15th IEEE International Conference on Data Mining Workshop, ICDMW 2015 - Atlantic City, United States
Duration: Nov 14 2015Nov 17 2015


Other15th IEEE International Conference on Data Mining Workshop, ICDMW 2015
CountryUnited States
CityAtlantic City


  • social media
  • topic detection
  • topic hierarchies

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Computer Science Applications

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