A survey on sentiment detection of reviews

  • Authors:
  • Huifeng Tang;Songbo Tan;Xueqi Cheng

  • Affiliations:
  • Information Security Center, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100080, PR China;Information Security Center, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100080, PR China;Information Security Center, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100080, PR China

  • Venue:
  • Expert Systems with Applications: An International Journal
  • Year:
  • 2009

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Abstract

The sentiment detection of texts has been witnessed a booming interest in recent years, due to the increased availability of online reviews in digital form and the ensuing need to organize them. Till to now, there are mainly four different problems predominating in this research community, namely, subjectivity classification, word sentiment classification, document sentiment classification and opinion extraction. In fact, there are inherent relations between them. Subjectivity classification can prevent the sentiment classifier from considering irrelevant or even potentially misleading text. Document sentiment classification and opinion extraction have often involved word sentiment classification techniques. This survey discusses related issues and main approaches to these problems.