Journal of Information Processing Systems

Korea Information Processing Society (한국정보처리학회)
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Microblog Sentiment Analysis Method Based on Spectral Clustering

  • Dong, Shi (School of Computer Science and Technology, Zhoukou Normal University) ;
  • Zhang, Xingang (School of Computer and Information Technology, Nanyang Normal University) ;
  • Li, Ya (School of Computer Science and Technology, Zhoukou Normal University)
  • Received : 2016.04.26
  • Accepted : 2017.02.01
  • Published : 2018.06.30
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Abstract

This study evaluates the viewpoints of user focus incidents using microblog sentiment analysis, which has been actively researched in academia. Most existing works have adopted traditional supervised machine learning methods to analyze emotions in microblogs; however, these approaches may not be suitable in Chinese due to linguistic differences. This paper proposes a new microblog sentiment analysis method that mines associated microblog emotions based on a popular microblog through user-building combined with spectral clustering to analyze microblog content. Experimental results for a public microblog benchmark corpus show that the proposed method can improve identification accuracy and save manually labeled time compared to existing methods.

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References

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