Sentiment Word Identification with Sentiment Contextual Factors

  • Jiguang LiangEmail author
  • Xiaofei Zhou
  • Yue Hu
  • Li Guo
  • Shuo Bai
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9313)


Sentiment word identification (SWI) refers to the task of automatically identifying whether a given word expresses positive or negative opinion. SWI is a critical component of sentiment analysis technologies. Traditional sentiment word identification techniques become unqualified because they need seed sentiment words which leads to low robustness. In this paper, we consider SWI as a matrix factorization problem and propose three models for it. Instead of seed words, we exploit sentiment matching and sentiment consistency for modeling. Extensive experimental studies on three real-world datasets demonstrate that our models outperform the state-of-the-art approaches.


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Jiguang Liang
    • 1
    Email author
  • Xiaofei Zhou
    • 1
  • Yue Hu
    • 1
  • Li Guo
    • 1
  • Shuo Bai
    • 1
  1. 1.National Engineering Laboratory for Information Security TechnologiesInstitute of Information Engineering, Chinese Academy of SciencesBeijingChina

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