Weifu Du
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.
- A. Andreevskaia and S. Bergler. 2008. When Specialists and Generalists Work Together: Overcoming Domain Dependence in Sentiment Tagging. In Proceedings of ACL-08: HLT.Google Scholar
- A. Aue and M. Gamon. 2005. Customizing Sentiment Classifiers to New Domains: a Case Study. In Proceedings of RANLP.Google Scholar
- J. Cohen. 1960. A coefficient of agreement for nominal scales. In: Educational and Psychological measurements 20, pp. 37--46.Google Scholar
- T. Cover and J. Thomas. 1991. Elements of Information Theory. John Wiley & Sons, New York. Google ScholarDigital Library
- A. Esuli and F. Sebastiani. 2005. Determining the semantic orientation of terms throush gloss classification. In Proceedings of CIKM. Google ScholarDigital Library
- A. Esuli and F. Sebastiani. 2006. SentiWordNet: A Publicly Available Lexical Resource for Opinion Mining. In Proceedings of LREC.Google Scholar
- M. Gamon and A. Aue. 2005. Automatic identification of sentiment vocabulary exploiting low association with known sentiment terms. In Proceedings of ACL. Google ScholarDigital Library
- V. Hatzivassiloglous and K. McKeown. 1997. Predicting the semantic orientation of adjectives. In Proceedings of ACL. Google ScholarDigital Library
- M. Hu and B. Liu. 2004. Mining and summarizing customer reviews. In Proceedings of KDD. Google ScholarDigital Library
- J. Kamps, M. Marx, R. Mokken, and M. Rijke. 2004. Using WordNet to measure semantic orientation of adjectives. In Proceedings of LREC.Google Scholar
- H. Kanayama, T. Nasukawa. 2006. Fully Automatic Lexicon Expansion for Domain-oriented Sentiment Analysis. In Proceedings of EMNLP. Google ScholarDigital Library
- S. Kim and E. Hovy. 2004. Determining the sentiment of opinions. In Proceedings of COLING. Google ScholarDigital Library
- B. Pang, L. Lee and S. Vaithyanathan. 2002. Thumbs up? Sentiment Classification using Machine Learning Techniques. In Proceedings of EMNLP. Google ScholarDigital Library
- A. Popescu and O. Etzioni. 2005. Extracting product features and opinions from reviews. In Proceedings of HLT/EMNLP. Google ScholarDigital Library
- N. Slonim, N. Tishby. 1999. Agglomerative information bottleneck. In Proceedings of NIPS.Google Scholar
- H. Takamura, T. Inui, M. Okumura. 2005. Extracting Semantic Orientations of Words using Spin Model. In Proceedings of ACL. Google ScholarDigital Library
- P. Turney. 2002. Thumbs up or thumbs down? semantic orientation applied to unsupervised classification of reviews. In Proceedings of ACL. Google ScholarDigital Library
- P. Turney and M. Littman. 2003. Measuring Praise and Criticism: Inference of Semantic Orientation from Association. In: ACM Transactions on Information Systems, 21(4): 315--346. Google ScholarDigital Library
- J. Wiebe, T. Wilson and M. Bell. 2001. Identifying Collocations for Recognizing Opinions. In Proceedings of the ACL/EACL Workshop on Collocation.Google Scholar
- H. Yu and V. Hatzivassiloglou. 2003. Towards Answering opinion Questions: Separating Facts from Opinions and Identifying the Polarity of Opinion Sentences. In Proceedings of EMNLP. Google ScholarDigital Library
- V. Stoyanov and C. Cardie. 2008. Topic Identification for Fine-Grained Opinion Analysis. In Proceedings of Coling. Google ScholarDigital Library
- H. Tang, S. Tan and X. Cheng. 2009. A Survey on Sentiment Detection of Reviews. Expert Systems with Applications. Google ScholarDigital Library
- S. Tan, G. Wu, H. Tang and X. Cheng. 2007. A novel scheme for domain-transfer problem in the context of sentiment analysis. In Proceedings of CIKM. Google ScholarDigital Library
- S. Tan, X. Cheng, Y. Wang, H. Xu. 2009. Adapting Naive Bayes to Domain Adaptation for Sentiment Analysis. In Proceedings of ECIR. Google ScholarDigital Library
- Q. Wu, S. Tan, H. Zhai, G. Zhang, M. Duan and X. Cheng. 2009. SentiRank: Cross-Domain Graph Ranking for Sentiment Classification. In Proceedings of WI. Google ScholarDigital Library
- W. Du, S. Tan. 2009. Building Domain-oriented Sentiment Lexicon by Improved Information Bottleneck. In Proceedings of CIKM. Google ScholarDigital Library
Index Terms
- Adapting information bottleneck method for automatic construction of domain-oriented sentiment lexicon
Recommendations
Building domain-oriented sentiment lexicon by improved information bottleneck
CIKM '09: Proceedings of the 18th ACM conference on Information and knowledge managementThis paper describes an adapted information bottleneck approach for construction of domain-oriented sentiment lexicon. The basic idea is to use three kinds of relationships (WWinter, WDinter and WDintra,) to infer the semantic orientation of the out-of-...
Automatic construction of a context-aware sentiment lexicon: an optimization approach
WWW '11: Proceedings of the 20th international conference on World wide webThe explosion of Web opinion data has made essential the need for automatic tools to analyze and understand people's sentiments toward different topics. In most sentiment analysis applications, the sentiment lexicon plays a central role. However, it is ...
A random walk algorithm for automatic construction of domain-oriented sentiment lexicon
Highlights► Proposes a random walk algorithm to construct domain-oriented sentiment lexicon. ► Utilizes sentiment words and documents from both old domain and target domain.► Simulates a random walk reflecting four relationships ...
AbstractIn recent years, many studies have been conducted to deal with automatic construction of domain-oriented sentiment lexicon. However, most of the attempts rely on only the relationship between sentiment words, failing to uncover the ...
Comments