LLT-PolyU: Identifying Sentiment Intensity in Ironic Tweets

SemEval 2015 - 9th International Workshop on Semantic Evaluation, co-located with the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2015 - Proceedings

Volumn , Issue , 2015, Pages 673-678

  Xu, Hongzhi ^a   Santus, Enrico ^a   Laszlo, Anna ^a   Huang, Chu Ren ^a  

^a HONG KONG POLYTECHNIC UNIVERSITY   (Hong Kong)

Author keywords

[No Author keywords available]

Indexed keywords

DECISION TREES; NATURAL LANGUAGE PROCESSING SYSTEMS; SEMANTICS;

CROSS VALIDATION; DECISION TREE REGRESSION; REGRESSION MODELLING; SUPPORT VECTOR REGRESSION MODELS; TRAINING DATA;

REGRESSION ANALYSIS;

EID: 84978848748     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (37)

1. Ahmed Abbasi, Hsinchun Chen, and Arab Salem. 2008. Sentiment analysis in multiple languages: Feature selection for opinion classification in web forums. ACM Transactions on Information Systems (TOIS), 26(3):12:1-12:34.
2. Stefano Baccianella, Andrea Esuli, and Fabrizio Sebastiani. 2010. Sentiwordnet 3.0: An enhanced lexical resource for sentiment analysis and opinion mining. In LREC, volume 10, pages 2200-2204.
3. Francesco Barbieri and Horacio Saggion. 2014. Modelling irony in twitter. In Proceedings of the Student Research Workshop at the 14th Conference of the European Chapter of the Association for Computational Linguistics, pages 56-64.
4. Francesco Barbieri, Francesco Ronzano, and Horacio Saggion. 2014. Italian irony detection in twitter: a first approach. In The First Italian Conference on Computational Linguistics CLiC-it 2014 & the Fourth International Workshop EVALITA 2014, pages 28-32.
5. Cristina Bosco, Viviana Patti, and Andrea Bolioli. 2013. Developing corpora for sentiment analysis and opinion mining: the case of irony and senti-tut. IEEE Intelligent Systems, 28(2):55-63.
6. Konstantin Buschmeier, Philipp Cimiano, and Roman K-linger. 2014. An impact analysis of features in a classification approach to irony detection in product reviews.
7. Paula Carvalho, Luís Sarmento, Mário J Silva, and Eugénio de Oliveira. 2009. Clues for detecting irony in user-generated contents: oh...!! it's so easy;-). In Proceedings of the 1st international CIKM workshop on Topic-sentiment analysis for mass opinion, pages 53-56. ACM.
8. Chih-Chung Chang and Chih-Jen Lin. 2011. Libsvm: A library for support vector machines. ACM Transactions on Intelligent Systems and Technology, 2:1-27.
9. Dmitry Davidov, Oren Tsur, and Ari Rappoport. 2010. Semi-supervised recognition of sarcastic sentences in twitter and amazon. In Proceedings of the Fourteenth Conference on Computational Natural Language Learning, pages 107-116.
10. Elena Filatova. 2012. Irony and sarcasm: Corpus generation and analysis using crowdsourcing. In Proceedings of Language Resources and Evaluation Conference, pages 392-398.
11. Aniruddha Ghosh, Guofu Li, Tony Veale, Paolo Rosso, Ekaterina Shutova, Antonio Reyes, and John Barn-den. 2015. Semeval-2015 task 11: Sentiment analysis of figurative language in twitter. In Proceedings of the International Workshop on Semantic Evaluation (SemEval-2015), Co-located with NAACL and *SEM, Denver, Colorado, US, June 4-5.
12. Andrea Gianti, Cristina Bosco, Viviana Patti, Andrea Bolioli, and Luigi Di Caro. 2012. Annotating irony in a novel italian corpus for sentiment analysis. In Proceedings of the 4th Workshop on Corpora for Research on Emotion Sentiment and Social Signals, pages 1-7.
13. Raymond W Gibbs and Herbert L Colston. 2007. Irony in language and thought: A cognitive science reader. Psychology Press.
14. Roberto González-Ibáñez, Smaranda Muresan, and Nina Wacholder. 2011. Identifying sarcasm in twitter: a closer look. In Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: short papers, volume 2, pages 581-586.
15. H Paul Grice, 1975. Logic and conversation, volume 3 of Syntax and Semantics, pages 41-58. Academic Press, New York.
16. Mark Hall, Eibe Frank, Geoffrey Holmes, Bernhard Pfahringer, Peter Reutemann, and Ian H. Witten. 2009. The weka data mining software: An update. SIGKDD Explorations, 11.
17. Yanfen Hao and Tony Veale. 2010. An ironic fist in a velvet glove: Creative mis-representation in the construction of ironic similes. Minds and Machines, 20(4):635-650.
18. Jennifer Hay. 2001. The pragmatics of humor support. International Journal of Humor Research, 14:1-27.
19. Minqing Hu and Bing Liu. 2004. Mining and summarizing customer reviews. In Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining, pages 168-177. ACM.
20. Dan Klein and Christopher D. Manning. 2003. Accurate unlexicalized parsing. In Proceedings of the 41st Annual Meeting on Association for Computational Linguistics-Volume 1, pages 423-430.
21. Helga Kotthoff. 2003. Responding to irony in different contexts: On cognition in conversation. Journal of pragmatics, 35(9):1387-1411.
22. Roger J Kreuz and Gina M Caucci. 2007. Lexical influences on the perception of sarcasm. In Proceedings of the Workshop on computational approaches to Figurative Language, pages 1-4.
23. Shoushan Li, Sophia Yat Mei Lee, Ying Chen, Chu-Ren Huang, and Guodong Zhou. 2010. Sentiment classification and polarity shifting. In Proceedings of the 23rd International Conference on Computational Linguistics, pages 635-643.
24. Christine Liebrecht, Florian Kunneman, and Antal van den Bosch. 2013. The perfect solution for detecting sarcasm in tweets# not. In Proceedings of the 4th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis. New Brunswick, NJ: ACL.
25. George Miller and Christiane Fellbaum. 1998. Wordnet: An electronic lexical database.
26. Finn Årup Nielsen. 2011. A new anew: Evaluation of a word list for sentiment analysis in microblogs. In Proceedings of the ESWC2011 Workshop on 'Making Sense of Microposts': Big things come in small packages.
27. Bo Pang and Lillian Lee. 2008. Opinion mining and sentiment analysis. Foundations and trends in information retrieval, 2(1-2):1-135.
28. Quintilian. 1922. With An English Translation. Harold Edgeworth Butler. Cambridge, Mass., Harvard University Press; London, William Heinemann, Ltd.
29. Antonio Reyes, Paolo Rosso, and Tony Veale. 2013. A multidimensional approach for detecting irony in twitter. Language Resources and Evaluation, 47(1):239-268.
30. Ellen Riloff, Ashequl Qadir, Prafulla Surve, Lalindra De Silva, Nathan Gilbert, and Ruihong Huang. 2013. Sarcasm as contrast between a positive sentiment and negative situation. In Proceedings of Conference on Emperical Methods for Natural Language Processing (EMNLP), pages 704-714.
31. Angus Stevenson. 2010. Oxford dictionary of English. Oxford University Press.
32. Frank Stringfellow Jr. 1994. The meaning of irony: A psychoanalytic investigation. SUNY Press.
33. Oren Tsur, Dmitry Davidov, and Ari Rappoport. 2010. Icwsm-a great catchy name: Semi-supervised recognition of sarcastic sentences in online product reviews. In In International AAAI Conference on Web and Social Media.
34. Piyoros Tungthamthiti, Shirai Kiyoaki, and Masnizah Mohd. 2014. Recognition of sarcasms in tweets based on concept level sentiment analysis and supervised learning approaches. In Proceedings of Pacific Asia Conference on Language, Information and Computing, Phuket, Thailand.
35. Andrea Vanzo, Giuseppe Castellucci, Danilo Croce, and Roberto Basili. 2014. A context based model for sentiment analysis in twitter for the italian language. In R. Basili, A. Lenci, and B. Magnini, editors, Proceedings of the First Italian Conference on Computational Linguistics CLiC-it & the Fourth International Workshop EVALITA, pages 379-383, Pisa. Pisa University Press.
36. Janyce Wiebe, Theresa Wilson, and Claire Cardie. 2005. Annotating expressions of opinions and emotions in language. Language resources and evaluation, 39(2-3):165-210.
37. Gongjun Yan, Wu He, Jiancheng Shen, and Chuanyi Tang. 2014. A bilingual approach for conducting chinese and english social media sentiment analysis. Computer Networks, 75:491-503.