The International Arab Journal of Information Technology (IAJIT)


Simultaneously Identifying Opinion Targets and Opinion-bearing Words Based on Multi-Features in Chinese Micro-Blog Texts

We propose to simultaneously identify opinion targets and opinion-bearing words based on multi-features in Chinese micro-blog texts, i.e., to identify opinion-bearing words by means of opinion-bearing words dictionary and to identify opinion targets by considering multi-features between opinion targets and opinion-bearing words, and then we take a future step to optimize forwarding-based opinion target identification. We decompose our task into four phases: 1) construct opinion-bearing words dictionary and identify opinion-bearing word in a sentence from Chinese micro-blog; 2) design multiple features related to opinion target identification, containing token, Part-Of-Speech (POS), Word Distance (WD), Direct Dependency Relation (DDR) and SRL; 3) design three kinds of different feature templates to identify feature-opinion pairs in Chinese micro-blog texts; 4) combining forwarding relation between individual micro-blogs, we solve the problem of identifying opinion target in short micro-blog. The experiments with Natural Language Processing (NLP) and Chinese Computing (CC) 2012 and 2013’s labeled data show that our approach provides better performance than the baselines and most systems reported at NLP and CC 2012 and 2013.

[1] Del-Corro L. and Gemulla R., “Clausie: Clause-Based Open Information Extraction,” in Proceeding of the 22nd International Conference on World Wide Web, Rio de Janeiro, pp. 355-366, 2013.

[2] Gokulakrishnan B., Priyanthan P., Ragavan T., Prasath N., and Perera A., “Opinion Mining and Sentiment Analysis on a Twitter Data Stream,” in Proceeding of International Conference on Advances in ICT for Emerging Regions, Colombo, pp. 182-188, 2012.

[3] Hu M. and Liu B., “Mining Opinion Features in Customer Reviews,” in Proceeding of The 19th National Conference on Artifical Intelligence, San Jose, pp. 755-760, 2004.

[4] Hu M. and Liu B., “Mining and Summarizing Customer Reviews,” in Proceeding of the 10th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Seattle, pp. 168-177, 2004.

[5] Jin W., Ho H., and Srihari R., “Opinionminer: A Novel Machine Learning System For Web Opinion Mining and Ex-Traction,” in Proceeding of the 15th ACM SIGKDD International Conference On Knowledge Discovery and Data Mining, Paris, pp. 1195-1204, 2009.

[6] Kaji N. and Kitsuregawa M., “Building Lexicon for Sentiment Analysis from Massive Collection of HTML Docu-Ments,” in Proceeding of the Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, Prague, pp.1075-1083, 2007.

[7] Kamal A., Abulaish M., and Anwar T., “Mining Feature-Opinion Pairs and Their Reliability Scores From Web Opinion Sources,” in Proceeding of the 2nd International Conference on Web Intelligence, Mining and Semantics, Craiova, pp. 15, 2012.

[8] Kanayama H. and Nasukawa T., “Fully Automatic Lexicon Expansion For Domain-Oriented Sentiment Analysis,” in Proceeding of the Conference on Empirical Methods in Natural Language Processing, Sydney, pp. 355-363, 2006.

[9] Kessler J. and Nicolov N., “Targeting Sentiment Expressions through Supervised Ranking of Linguistic Configurations,” in Proceeding of the 3 rd International AAAI Conference on Weblogs and Social Media, San Jose, pp. 90-97, 2009.

[10] Khan K., Baharudin B., and Khan A., “Identifying Product Features from Customer Reviews Using Hybrid Dependency Patterns,” The International Arab Journal of Information Technology, vol. 11, no. 3, pp. 281-286, 2012.

[11] Liu Q., Feng C., and Huang H., “Emotional Tendency Identification for Micro-blog Topics Based on Multiple Characteristics,” in Proceeding of the 26th Pacific Asia Conference on Language, Information and Computation, Bali, pp. 304-312, 2012.

[12] Lu B., “Identifying Opinion Holders and Targets with Dependency Parser in Chinese News Texts,” in Proceeding of the NAACL HLT 2010 Student Research Workshop, Los Angeles, pp. 46-51, 2010.

[13] Popescu A. and Etzioni O., Natural Language Processing and Text Mining, Springer London, 2007.

[14] Qiu G., Liu B., Bu J., and Chen C., “Expanding Domain Sentiment Lexicon Through Double Propagation,” in Proceeding of the 21st International Joint Conference on Artificial Intelligence, California, pp. 1199-1204, 2009.

[15] Xu L., Liu K., Lai S., Chen Y., and Zhao J., “Mining Opinion Words and Opinion Targets in a Two-Stage Frame-work,” in Proceeding of the 51st Annual Meeting of the Association for Computation Linguistics, Sofia, pp. 1764-1773, 2013.

[16] Yang B. and Cardie C., “Joint Inference for Fine-Grained Opinion Extraction,” in Proceeding of the 51st Annual Meeting of the Association for Computational Linguistics, Sofia, pp. 1640-1649, 2013.