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Two-Phase Computing Model for Chinese Microblog Sentimental Analysis

  • Jianyong DuanEmail author
  • Chao Wang
  • Mei Zhang
  • Hui Liu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9714)

Abstract

The sentimental analysis of Chinese microblog is a crucial task for social network related applications, such as internet marketing, public opinion monitoring, etc. This paper proposes a two-phase computing model for microblog sentimental analysis, including topic classification for posts and topic sentimental analysis respectively. In the first phase, the Latent Dirichlet Allocation(LDA) model is employed into our model for topic classification. The topics of posts are scattered into the microblogs, it has some uncertainty. The LDA model can classify the fuzzy topics. In the second phase, sentimental dictionary and emotion knowledge are performed into our model for topic sentimental analysis. HowNet as the sentimental dictionary is used to the sentimental tendency analysis. The emotion knowledge mainly uses symbols in microblog. Besides of sentimental knowledge, the sliding window for sentimental analysis also introduced into the model as the modification at the sentence level. The experimental results show that this method achieves good performance.

Keywords

Sentimental analysis Knowledge base LDA model Sliding window 

Notes

Acknowledgment

The authors are grateful to the reviewers for reviewing this paper. This work is supported by the National Science Foundation of China (Grant No.61103112), Social Science Foundation of Beijing(Grant No.13SHC031), Ministry of Education of China (Project of Humanities and Social Sciences, Grant NO.13YJC740055) and Beijing Young talent plan(Grant No.CIT&TCD201404005)

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.College of Computer ScienceNorth China University of TechnologyBeijingPeople’s Republic of China
  2. 2.Business Information Management SchoolShanghai Institute of Foreign TradeShanghaiPeople’s Republic of China

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