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Classification of Micro-blog Sentiment Based on Naive Bayesian Classifier

In: Liss 2013

Author

Listed:
  • Xiaoheng Ou

    (Dalian Maritime University)

  • Yan Cao

    (Dalian Maritime University)

  • Xiangwei Mu

    (Dalian Maritime University)

Abstract

This paper is to conduct popular micro-blog for sentiment classification. The Naive Bayesian Classifier is the key in this paper, and study on pretreatment of the text of micro-blog, constructing sentiment dictionary, feature selection, feature weights and expression vector, comes up with some points and conducts the experiment. And the performance of “emoticons + twice sentiment feature extraction + BOOL” is the best pretreatment method. And this experiment gains a relatively satisfactory result.

Suggested Citation

  • Xiaoheng Ou & Yan Cao & Xiangwei Mu, 2015. "Classification of Micro-blog Sentiment Based on Naive Bayesian Classifier," Springer Books, in: Runtong Zhang & Zhenji Zhang & Kecheng Liu & Juliang Zhang (ed.), Liss 2013, pages 585-589, Springer.
    • Handle: RePEc:spr:sprchp:978-3-642-40660-7_86
    DOI: 10.1007/978-3-642-40660-7_86
    as

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