LDA-Based Topic Strength Analysis

Authors

  • Jiamiao Wang School of Computer Science and Information Engineering, Hefei University of Technology
  • Lei Li School of Computer Science and Information Engineering, Hefei University of Technology
  • Xindong Wu School of Computing and Informatics, University of Louisiana at Lafayette

Keywords:

LDA (latent Dirichlet allocation), topic strength

Abstract

Topic strength is an important hotspot in topic research. The evolution of topic strength not only indicates emerging new topics, but also helps us to determine whether a topic will produce some fluctuation of topic strength over time. Thus, topic strength analysis can provide significant findings in public opinion monitoring and user personalization. In this paper, we present an LDA-based topic strength analysis approach. We take topic quality into our topic strength consideration by combining local LDA and global LDA. For empirical studies, we use three data sets in real applications: film critic data of "A Chinese Odyssey" in Douban Movies, corruption news data in Sina News, and public paper data. Compared to existing approaches, experimental results show that our proposed approach can obtain better results of topic strength analysis in detecting the time of event topic occurrences and distinguishing different types of topics, and it can be used to monitor the occurrences of public opinions and the changes of public concerns.

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How to Cite

Wang, J., Li, L., & Wu, X. (2018). LDA-Based Topic Strength Analysis. COMPUTING AND INFORMATICS, 36(6), 1283–1311. Retrieved from http://www.cai.sk/ojs/index.php/cai/article/view/2017_6_1283

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