Sentiment analysis with global topics and local dependency

Proceedings of the National Conference on Artificial Intelligence

Volumn 3, Issue , 2010, Pages 1371-1376

  Li, Fangtao ^a   Huang, Minlie ^a   Zhu, Xiaoyan ^a  

^a TSINGHUA UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; MARKOV PROCESSES; SENTIMENT ANALYSIS;

EFFECTIVE APPROACHES; LDA MODELS; LOCAL CONTEXTS; RESEARCH PROBLEMS; SIMULTANEOUS ANALYSIS; TOPIC MODEL; TOPIC MODELING; WEB 2.0;

DATA MINING;

EID: 77958578169     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (18)

1. D. M. Blei, A. Y. Ng, and M. I. Jordan. 2003. Latent dirichlet allocation. J. Mach. Learn. Res., 3:993-1022.
2. John Blitzer, Mark Dredze, Fernando Pereira. 2007. Biographies, Bollywood, Boom-boxes and Blenders: Domain Adaptation for Sentiment Classification. Association for Computational Linguistics (ACL).
3. Hang Cui, Vibhu Mittal and Mayur Datar. 2006. Comparative Experiments on Sentiment Classification for Online Product Reviews. In Proceedings of the Twenty-First National Conference on Artificial Intelligence (AAAI-06).
4. Kerstin Denecke. 2009. Are SentiWordNet Scores Suited for Multi-Domain Sentiment Classification? In 4th International Conference on Digital Information Management, ICDIM.
5. X. Ding and B. Liu. 2007. The utility of linguistic rules in opinion mining. In Proceedings of the 30th Annual international ACM SIGIR Conference.
6. T.L. Griffiths, M. Steyvers, D.M. Blei, and J.B. Tenenbaum. 2005. Integrating Topics and Syntax. In: Advances in Neural Information Processing Systems, 17 (Saul, L.K et al., eds), 537-544.
7. Amit Gruber, Michal Rosen-Zvi and Yair Weiss. 2007. "Hidden Topic Markov Models," in Artificial Intelligence and Statistics (AISTATS), San Juan, Puerto Rico.
8. Thomas Hof mann. 1999. Probabilistic Latent Semantic Indexing, Proceedings of the Twenty-Second Annual International SIGIR Conference (SIGIR-99).
9. Jing Jiang. 2009. "Modeling syntactic structures of topics with a nested HMM-LDA" In Proceedings of ICDM.
10. Bing Liu. 2010. Sentiment Analysis and Subjectivity. To appear in Handbook of natural Language Processing, Second Edition.
11. C. Lin, and Y. He. 2009. Joint Sentiment/Topic Model for Sentiment Analysis, The 18th ACM Conference on Information and Knowledge Management (CIKM).
12. Q. Mei, X. Ling, M. Wondra, H. Su, and C. Zhai. 2007. Topic sentiment mixture: modeling facets and opinions in weblogs. In Proceedings of the 16th international conference on World Wide Web, pages 171-180.
13. B. Pang, L. Lee, and S. Vaithyanathan. 2002. Thumbs up?: sentiment classification using machine learning techniques. In Proceedings of the conference on Empirical methods in natural language processing, pages 79-86.
14. Bo Pang and Lillian Lee. 2008. Opinion mining and sentiment analysis. Foundations and Trends in Information Retrieval 2(1-2), pp. 1-135.
15. I. Titov and R. McDonald. 2008. Modeling online reviews with multi-grain topic models. In WWW '08: Proceeding of the 17th international conference on World Wide Web, pages 111-120, New York, NY, USA.
16. P. D. Turney. 2002. Thumbs up or thumbs down?: semantic orientation applied to unsupervised classification of reviews. In Proceedings of the 40th Annual Meeting on Association for Computational Linguistics.
17. H. M. Wallach. 2006. Topic modeling: beyond bag-of - words. In ICML: Proceedings of the 23rd international conference on Machine learning, pages 977-984.
18. Theresa Wilson, Janyce Wiebe, and Paul Hoffmann. 2005. Recognizing Contextual Polarity in Phrase-Level Sentiment Analysis. Proc. of HLT-EMNLP-2005.