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A method of building Chinese microblog sentiment lexicon

ZHOU Yongmei1, YANG Aimin1, LIN Jianghao2   

  1. 1.Cisco School of Informatics, Guangdong University of Foreign Studies, Guangzhou 510006, Guangdong, China;
    2. School of Management, Guangdong University of Foreign Studies, Guangzhou 510006, Guangdong, China
  • Received:2013-04-30 Online:2014-06-20 Published:2013-04-30

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Abstract:

A method of building Chinese microblog sentiment lexicon was proposed,which adopted the discovery strategies of context entropy for network language, acquired network languages from the secondary filtration by TF-IDF and computed the sentiment weights of network language by SO-PMI algorithm in the labeled corpus. The built lexicon was applied into the analysis experiments of micro-blog sentiment,which was compared with that of naive bayesian classifier. Experiment results showed that the efficacy of classification by the built micro-blog sentimental lexicon was better than that by naive bayesian classifier,and was simple and rapid in the classification process.

Key words: sentiment analysis, context entropy, microblog sentiment lexicon, network languages, naive Bayesian

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