A polarity analysis framework for Twitter messages

Applied Mathematics and Computation

Volumn 270, Issue , 2015, Pages 756-767

  Lima, Ana Carolina E S ^a,b   De Castro, Leandro Nunes ^a   Corchado, Juan M ^b  

^a MACKENZIE PRESBYTERIAN UNIVERSITY   (Brazil)

^b UNIVERSITY OF SALAMANCA   (Spain)

Author keywords

Classification task; Machine learning; Sentiment analysis; Social media; Text mining; Twitter

Indexed keywords

ARTIFICIAL INTELLIGENCE; BIG DATA; DATA MINING; DECISION TREES; LEARNING SYSTEMS; NATURAL LANGUAGE PROCESSING SYSTEMS; NEAREST NEIGHBOR SEARCH; SOCIAL NETWORKING (ONLINE); SUPPORT VECTOR MACHINES; TEXT PROCESSING;

CLASSIFICATION TASKS; SENTIMENT ANALYSIS; SOCIAL MEDIA; TEXT MINING; TWITTER;

LEARNING ALGORITHMS;

EID: 84940981567     PISSN: 00963003     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.amc.2015.08.059     Document Type: Article

References (59)

1. M. Perc The Matthew effect in empirical data J. R. Soc. Interface 11 2014 1 15
2. J. Gao, J. Hu, X. Mao, M. Perc Culturomics meets random fractal theory: insights into long-range correlations of social and J. R. Soc. Interface 9 2012 1956 1964
3. M. Perc Evolution of the most common English words and phrases over the centuries J. R. Soc. Interface 12 2012 1 6
4. J. Park, V. Barash, C. Fink, M. Cha Emoticon style: interpreting differences in emoticons across cultures Proceedings of the Seventh International AAAI Conference on Weblogs and Social Media (ICWSM) 2013 466 475
5. M. Tsytsarau, T. Palpanas survey on mining subjective data on the web Ingegneria e Scienza dell'Informazione 2010 University of Trento, Trento, Relatório Técnico DISI-10-045
6. Datasift. (2012) Browse data sources - Twitter. [Online]. Available from: http://datasift.com/source/6/twitter (accessed: 12.04.12).
7. H. Tang, S. Tan, X. Cheng A survey on sentiment detection of reviews J. Exp. Syst. Appl. Int. J. Arch. 36 2009 10760 10773
8. A. Agarwal, B. Xie, I. Vovsha, O. Rambow, R. Passonneau Sentiment analysis of Twitter data Proceedings of the Workshop on Languages in Social Media 2011 30 38
9. S. Bhuta, A. Doshi, U. Doshi, M. Narvekar A review of techniques for sentiment analysis of Twitter data Issues and Challenges in Intelligent Computing Techniques (ICICT), 2014 International Conference on Ghaziabad, India 2014 583 591
10. P.S. Earle, D.C. Bowden, M. Guy Twitter earthquake detection: earthquake monitoring in a social world Ann. Geophys 54 2011 708 715
11. F. Abel, C. Hauff, G.-J. Houben, R. Stronkman, K. Tao Twitcident: fighting fire with information from social web streams Proceedings of the 21st International Conference Companion on World Wide Web 2012 305 308
12. M. Yoshida, S. Matsushima, S. Ono, I. Sato, H. Nakagawa ITC-UT: tweet categorization by query categorization of on-line reputation management Conference on Multilingual and Multimodal Information Access Evaluation 2010
13. A. Tumasjan, T.O. Sprenger, P.G. Sandner, I.M. Welpe Predicting elections with Twitter: what 140 characters reveal about political sentiment Proceedings of the Fourth International AAAI Conference on Weblogs and Social Media 2010 AAAI
14. A. Bermingham, A. Smeaton On using Twitter to monitor political sentiment and predict election results Proceedings of the Sentiment Analysis Where AI Meets Psychology 2011 2 10
15. J. Bollen, H. Mao, X. Zeng Twitter mood predicts the stock market J. Comput. Sci. 2 2011 1 8
16. F. Botta, H.S. Moat, T. Preis Quantifying crowd size with mobile phone and Twitter data R. Soc. Open Sci. 2 2015 1 6
17. C.M. Alis et al. Quantifying regional differences in the length of Twitter messages PLoS One 10 2015 1 10
18. S. Salustiano O Profissional Analista Para entender o Monitoramento de Mídias Sociais 2012 34 40
19. Elife. (2012) Serviços. [Online]. Avaliable from: http://elife.com.br/servicos/ (accessed: 30.05.13).
20. B. Pang, L. Lee Opinion mining and sentiment analysis Found. Trends Inform. Retriev. 2 2008 1 135
21. N.R.S. Filho Monitoramento das redes sociais como forma de relacionamento com o consumidor. O que as empresas estão fazendo? Gestão Contemp. 1 2011 63 86
22. H. Yu, V. Hatzivassiloglou Towards answering opinion questions: separating facts from opinions and identifying the polarity of opinion sentences Proceedings of the 2003 Conference on Empirical Methods in Natural Language Processing 2003 129 136
23. A. Yessenalina, Y. Yue, C. Cardie Multi-level structured models for document-level sentiment classification Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing Cambridge, MA 2010 1046 1056
24. T. Wilson, J. Wiebe, P. Hoffmann Recognizing contextual polarity in phrase-level sentiment analysis Proceedings of the Conference on Human Language Technology and Empirical Methods in Natural Language Processing Vancouver, British Columbia, Canada 2005 347 354
25. A.B. Sayeed, J. Boyd-Graber, B. Rusk, A. Weinberg Grammatical structures for word-level sentiment detection Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies Montreal, Canada 2012 667 676
26. X. Wang, F. Wei, X. Liu, M. Zhou, M. Zhang Topic sentiment analysis in Twitter: a graph-based hashtag sentiment classification approach Proceedings of the 20th ACM International Conference on Information and Knowledge Management Glasgow, Scotland, UK 2011 1031 1040
27. A. Kumar, T.M. Sebastian Sentiment analysis: a perspective on its past, present and future Intell. Syst. Appl. 4 2012 1 14
28. N.A. Diakopoulos, D.A. Shamma Characterizing debate performance via aggregated Twitter sentiment Proceedings of the SIGCHI Conference on Human Factors in Computing Systems Atlanta, GA, USA 2010 1195 1198
29. M. Thelwall, K. Buckley, G. Paltoglou, D. Cai, A. Kappas Sentiment strength detection in short informal text J. Am. Soc. Inform. Sci. Technol. 62 2010 2544 2558
30. L.M. Santos Protótipo para mineração de opinião em redes sociais: estudo de casos selecionados usando o Twitter 2010 Universidade Federal de Lavras, Lavras - MG Monografia (Graduação em Ciência da Computação)
31. J. Wiebe, T. Wilson, R. Bruce, M. Bell, M. Martin Learning subjective language Comput. Linguist. 30 2004 277 308
32. C.D. Manning, P. Raghavan, H. Schütze Introduction to Information Retrieval 2008 Cambridge University Press
33. A. Kumar, T.M. Sebastian Machine learning assisted sentiment analysis Proceedings of International Conference on Computer Science & Engineering 2012 123 130
34. Y.R. Tausczik, J.W. Pennebaker The psychological meaning of words: Liwc and computerized text analysis methods J. Lang. Social Psychol. 29 2010 24 54
35. A. Esuli, F. Sebastiani SentiWordNet: a publicly available lexical resource for opinion mining Conference on Language Resources and Evaluation 2006 417 422
36. M. Annett, G. Kondrak A comparison of sentiment analysis techniques: polarizing movie blogs Proceedings of the Canadian Society for Computational Studies of Intelligence, 21st Conference on Advances in Artificial Intelligence 2008 25 35
37. A. Go, R. Bhayani, L. Huang Twitter Sentiment Classification using Distant Supervision'' Technical report 2009 Stanford Digital Library Technologies Project
38. T. Lake Twitter Sentiment Analysis 2011 Western Michigan University, For client William Fitzgerald Kalamazoo, MI
39. J. Bollen, H. Mao, A. Pepe Modeling public mood and emotion: Twitter sentiment and socio-economic phenomena Proceedings of the Fifth International AAAI Conference on Weblogs and Social Media 2011 450 453
40. B. Pang, L. Lee, S. Vaithyanathan Thumbs up?: sentiment classification using machine learning techniques Proceedings of the ACL-02 Conference on Empirical Methods in Natural Language Processing 10 2002 79 86
41. R. Prabowo, M. Thelwall Sentiment analysis: a combined approach J. Informetrics 3 2009 143 157
42. J. Read Using emoticons to reduce dependency in machine learning techniques for sentiment classification Proceedings of the ACL Student Research Workshop 2005 43 48
43. M. Araújo, P. Gonçalves, F. Benevenuto Métodos para análise de sentimentos no Twitter Proceedings of the Simpósio Brasileiro de Sistemas Multimídia e Web (WEBMEDIA) Salvador 2013
44. A. Bakliwal et al. Mining sentiments from Tweets Proceedings of the 3rd Workshop in Computational Approaches to Subjectivity and Sentiment Analysis Jeju, Republic of Korea 2012 11 18
45. N.F.F. da Silva, E.R. Hruschka, E.R. Hruschka Jr. Tweet sentiment analysis with classifier ensembles Decis. Support Syst. 66 2014 170 179
46. F.H. Khan, S. Bashir, U. Qamar TOM: Twitter opinion mining framework using hybrid classification scheme Decis. Support Syst. 57 2014 245 257
47. M.M. Bradley and P.J. Lang (2013, January) ANEW Message. [Online]. Available from: http://csea.phhp.ufl.edu/media/anewmessage.html (accessed: 15.09.14).
48. D. Watson, L.A. Clark THE PANAS-X Manual for the Positive and Negative Affect Schedule - Expanded Form 1994 The University of Iowa Iowa
49. E. Cambria, A. Hussain Sentic Computing: Techniques, Tools, and Applications 2012 Springer Dordrecht, Netherlands
50. I.H. Witten Text Mining. In Practical Handbook of Internet Computing 2005 Chapman & Hall/CRC Press Florida
51. J.W. Pennebaker, M.E. Francis Linguistic Inquiry and Word Count 1999 Lawrence Erlbaum
52. J.W. Pennebaker, R.J. Booth, M.E. Francis Linguistic Inquiry and Word Count: LIWC2007 - Operator's Manual 2007 LIWC.net Austin, Texas
53. K. Toutanova, C.D. Manning Enriching the knowledge sources used in a maximum entropy part-of-speech Tagger Proceedings of the 2000 Joint SIGDAT Conference on Empirical Methods in Natural Language Processing and Very Large Corpora: Held in Conjunction with the 38th Annual Meeting of the Association for Computational Linguistics - Volume 13 Hong Kong 2000 63 70
54. E.S. Atwell, J. Hughes, C. Souter AMALGAM: automatic mapping among lexico-grammatical annotation models Workshop On The Balancing Act: Combining Symbolic And Statistical Approaches To Language 1994
55. C. Fellbaum WordNet: An Electronic Lexical Database 1998 MIT Press Cambridge, MA
56. D.A. Shamma, L. Kennedy, E.F. Churchill Tweet the debates: understanding community annotation of uncollected sources Proceedings of the First SIGMM Workshop on Social Media Beijing, China 2009 3 10
57. I.H. Witten, E. Frank, M.A. Hall Data Mining: Practical Machine Learning Tools and Techniques 3rd ed. 2011 Morgan Kaufmann
58. I.H. Witten Text mining. In Practical Handbook of Internet Computing 2005 Chapman & Hall/CRC Press Florida
59. J. Han, M. Kamber, Jian Pei Data Mining: Concepts and Techniques 3rd ed. 2011 Morgan Kaufmann Publishers