Journal of Northeastern University ›› 2013, Vol. 34 ›› Issue (4): 490-493.DOI: -

• Information & Control • Previous Articles     Next Articles

Detecting Topical Opinion Leaders Based on LDA Model in Chinese Microblogs

FENG Shi, JING Shan, YANG Zhuo, WANG Daling   

  1. School of Information Science & Engineering, Northeastern University, Shenyang 110819, China.
  • Received:2012-10-22 Revised:2012-10-22 Online:2013-04-15 Published:2013-06-19
  • Contact: FENG Shi
  • About author:-
  • Supported by:
    -

Abstract: How to effectively detect the opinion leaders in the Chinese microblog space has become a hot research problem in the related area. To tackle this issue, an algorithm combined LDA model and HowNet was proposed to classify the short texts in microblogs based on their underlying subtopics. Then an influence measurement containing the criteria on explicit, implicit and user features was introduced. An analytic hierarchy process method was employed to assign different weight of each parameter. Experiment results showed that the proposed short text classification method outperformed the traditional SVM based method, and the proposed influence measurement model could effectively detect the opinion leaders in the Chinese hot topic microblogs.

Key words: microblog, short text classification, opinion leader, sentiment analysis, LDA

CLC Number: