A probabilistic approach to tweets' sentiment classification

Proceedings - 2013 Humaine Association Conference on Affective Computing and Intelligent Interaction, ACII 2013

Volumn , Issue , 2013, Pages 37-42

  Colace, Francesco ^a   De Santo, Massimo ^a   Greco, Luca ^a  

^a UNIVERSITY OF SALERNO   (Italy)

Author keywords

Information extraction management; Latent dirichlet allocation; Sentiment analysis

Indexed keywords

EXPERIMENTAL EVALUATION; GRAPHICAL MODEL; LATENT DIRICHLET ALLOCATION; LATENT DIRICHLET ALLOCATIONS; PROBABILISTIC APPROACHES; REAL TIME ANALYSIS; SENTIMENT ANALYSIS; SENTIMENT CLASSIFICATION;

DATA MINING; SOCIAL NETWORKING (ONLINE); STATISTICS;

ASSOCIATION REACTIONS;

EID: 84893270093     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ACII.2013.13     Document Type: Conference Paper

References (21)

1. Wordnet - http://wordnet.princeton.edu/.
2. Marco Baroni and Stefano Vegnaduzzo. Identifying subjective adjectives through web-based mutual information. In In Proceedings of the 7th Konferenz zur Verarbeitung Natrlicher Sprache (German Conference on Natural Language Processing KONVENS04, pages 613-619, 2004.
3. David M. Blei, Andrew Y. Ng, and Michael I. Jordan. Latent dirichlet allocation. J. Mach. Learn. Res., 3:993-1022, March 2003.
4. E. Cambria, Y. Song, H. Wang, and N. Howard. Semantic multidimensional scaling for open-domain sentiment analysis, 2013.
5. F. Clarizia, F. Colace, M. De Santo, L. Greco, and P. Napoletano. Mixed graph of terms for query expansion. In Intelligent Systems Design and Applications (ISDA), 2011 11th International Conference on, pages 581-586, 2011.
6. Richard Colbaugh and Kristin Glass. Estimating sentiment orientation in social media for intelligence monitoring and analysis. In Intelligence and Security Informatics (ISI), 2010 IEEE International Conference on, pages 135-137, may 2010.
7. Michael Gamon and Anthony Aue. Automatic identification of sentiment vocabulary: Exploiting low association with known sentiment terms. In Proceedings of the ACL Workshop on Feature Engineering for Machine Learning in Natural Language Processing, pages 57-64, Ann Arbor, Michigan, June 2005. Association for Computational Linguistics.
8. Thomas L. Griffiths, Joshua B. Tenenbaum, and Mark Steyvers. Topics in semantic representation. Psychological Review, 114:2007, 2007.
9. Thomas Hofmann. Probabilistic latent semantic analysis. In In Proc. of Uncertainty in Artificial Intelligence, UAI99, pages 289-296, 1999.
10. Bing Liu. Sentiment analysis and subjectivity. In Handbook of Natural Language Processing, Second Edition. Taylor and Francis Group, Boca, 2010.
11. P. Napoletano, F. Colace, M. De Santo, and L. Greco. Text classification using a graph of terms. In Complex, Intelligent and Software Intensive Systems (CISIS), 2012 Sixth International Conference on, pages 1030-1035, July.
12. A. Neviarouskaya, H. Prendinger, and M. Ishizuka. Sentiful: A lexicon for sentiment analysis. Affective Computing, IEEE Transactions on, 2(1):22-36, jan.-june 2011.
13. Bo Pang and Lillian Lee. Opinion mining and sentiment analysis. Found. Trends Inf. Retr., 2(1-2):1-135, January 2008.
14. Bo Pang, Lillian Lee, and Shivakumar Vaithyanathan. Thumbs up? sentiment classification using machine learning techniques. In Proceedings of EMNLP, pages 79-86, 2002.
15. Rudy Prabowo and Mike Thelwall. Sentiment analysis: A combined approach. Journal of Informetrics, 3:143-157, 2009.
16. Fabrizio Sebastiani and Consiglio Nazionale Delle Ricerche. Machine learning in automated text categorization. ACM Computing Surveys, 34:1-47, 2002.
17. Khin Phyu Phyu Shein. Ontology based combined approach for sentiment classification. In Proceedings of the 3rd International Conference on Communications and information technology, CIT'09, pages 112-115, Stevens Point, Wisconsin, USA, 2009. World Scientific and Engineering Academy and Society (WSEAS).
18. P. Turney and M. Littman. Unsupervised learning of semantic orientation from a hundred-billion-word corpus. Technical report nrc technical report erb-1094, Institute for Information Technology, National Research Council Canada, 2002.
19. Hao Wang, Dogan Can, Abe Kazemzadeh, François Bar, and Shrikanth Narayanan. A system for real-time twitter sentiment analysis of 2012 u.s. presidential election cycle. In Proceedings of the ACL 2012 System Demonstrations, ACL '12, pages 115-120, Stroudsburg, PA, USA, 2012. Association for Computational Linguistics.
20. Theresa Wilson, Janyce Wiebe, and Rebecca Hwa. Just how mad are you? finding strong and weak opinion clauses. In Proceedings of the 19th national conference on Artifical intelligence, AAAI'04, pages 761-767. AAAI Press, 2004.
21. Xiaohui Yu, Yang Liu, Xiangji Huang, and Aijun An. Mining online reviews for predicting sales performance: A case study in the movie domain. IEEE Trans. on Knowl. and Data Eng., 24(4):720-734, April 2012.