Adapting information bottleneck method for automatic construction of domain-oriented sentiment lexicon

Authors:
Weifu Du;Songbo Tan;Xueqi Cheng;Xiaochun Yun
Affiliations:
Haerbin Institute of Technology, Haerbin, China;Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China;Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China;Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China
Venue:
Proceedings of the third ACM international conference on Web search and data mining
Year:
2010

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Abstract

Domain-oriented sentiment lexicons are widely used for fine-grained sentiment analysis on reviews; therefore, the automatic construction of domain-oriented sentiment lexicon is a fundamental and important task for sentiment analysis research. Most of existing construction approaches take only the kind of relationships between words into account, which makes them have a lot of room for improvement. This paper proposes an adapted information bottleneck method for the construction of domain-oriented sentiment lexicon. This approach can naturally make full use of the mutual reinforcement between documents and words by fusing three kinds of relationships either from words to documents or from words to words; either homogeneous or heterogeneous; either within-domain or cross-domain. The experimental results demonstrate that proposed method could dramatically improve the accuracy of the baseline approach on the construction of out-of-domain sentiment lexicon.