Parsing-based sarcasm sentiment recognition in Twitter data

Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015

Volumn , Issue , 2015, Pages 1373-1380

  Bharti, Santosh Kumar ^a   Babu, Korra Sathya ^a   Jena, Sanjay Kumar ^a  

^a NATIONAL INSTITUTE OF TECHNOLOGY   (India)

Author keywords

Natural language processing; Opinion mining; Parsing; Sarcasm; Sentiment; Tweets

Indexed keywords

DATA MINING; SOCIAL NETWORKING (ONLINE);

NATURAL LANGUAGE PROCESSING; OPINION MINING; PARSING; SARCASM; SENTIMENT; TWEETS;

NATURAL LANGUAGE PROCESSING SYSTEMS;

EID: 84962592138     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2808797.2808910     Document Type: Conference Paper

References (21)

1. R. González-Ibánez, S. Muresan, and N. Wacholder, "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-vol 2, pp. 581-586, 2011.
2. R. J. Kreuz and G. M. Caucci, "Lexical influences on the perception of sarcasm," in Proceedings of the Workshop on computational approaches to Figurative Language, ACL, pp. 1-4, 2007.
3. C. Liebrecht, F. Kunneman, and A. van den Bosch, "The perfect solution for detecting sarcasm in tweets# not," Association for Computational Linguistics, pp. 29-37, 2013.
4. E. Riloff, A. Qadir, P. Surve, L. De Silva, N. Gilbert, and R. Huang, "Sarcasm as contrast between a positive sentiment and negative situation.," in EMNLP, pp. 704-714, 2013.
5. E. Lunando and A. Purwarianti, "Indonesian social media sentiment analysis with sarcasm detection," in Advanced Computer Science and Information Systems (ICACSIS), 2013 International Conference on IEEE, pp. 195-198, 2013.
6. F. Barbieri, H. Saggion, and F. Ronzano, "Modelling sarcasm in twitter, a novel approach," in Association for Computational Linguistics, pp. 50-58, 2014.
7. D. Davidov, O. Tsur, and A. Rappoport, "Semi-supervised recognition of sarcastic sentences in twitter and amazon," in Proceedings of the Fourteenth Conference on Computational Natural Language Learning, pp. 107-116, 2010, Association for Computational Linguistics.
8. E. Filatova, "Irony and sarcasm: Corpus generation and analysis using crowdsourcing.," in LREC, pp. 392-398, 2012.
9. R. Justo, T. Corcoran, S. M. Lukin, M. Walker, and M. I. Torres, "Extracting relevant knowledge for the detection of sarcasm and nastiness in the social web," Knowledge-Based Systems, vol. 69, pp. 124-133, 2014.
10. F. Kunneman, C. Liebrecht, M. van Mulken, and A. van den Bosch, "Signaling sarcasm: From hyperbole to hashtag," Information Processing & Management (in press), 2014.
11. P. Liu, W. Chen, G. Ou, T. Wang, D. Yang, and K. Lei, "Sarcasm detection in social media based on imbalanced classification," in Web-Age Information Management, pp. 459-471, 2014.
12. D. Maynard and M. A. Greenwood, "Who cares about sarcastic tweets? investigating the impact of sarcasm on sentiment analysis," in Proceedings of LREC, pp. 4238-4243, 2014.
13. O. Tsur, D. Davidov, and A. Rappoport, "Icwsm - a great catchy name: Semi-supervised recognition of sarcastic sentences in online product reviews.," in ICWSM, pp. 162-169, 2010.
14. D. Tayal, S. Yadav, K. Gupta, B. Rajput, and K. Kumari, "Polarity detection of sarcastic political tweets," in Computing for Sustainable Global Development (INDIACom), 2014 International Conference on IEEE, pp. 625-628, 2014.
15. A. Rajadesingan, R. Zafarani, and H. Liu, "Sarcasm detection on twitter: A behavioral modeling approach," in Proceedings of the Eighth ACM International Conference on Web Search and Data Mining, pp. 97-106, 2015.
16. P. Tungthamthiti, K. Shirai, and M. Mohd, "Recognition of sarcasm in tweets based on concept level sentiment analysis and supervised learning approaches," pp. 404-413, 2014.
17. R. J. Kreuz and R. M. Roberts, "Two cues for verbal irony: Hyperbole and the ironic tone of voice," Metaphor and symbol, vol. 10, no. 1, pp. 21-31, 1995.
18. A. Utsumi, "Verbal irony as implicit display of ironic environment: Distinguishing ironic utterances from nonirony," Journal of Pragmatics, vol. 32, no. 12, pp. 1777-1806, 2000.
19. J. W. Pennebaker, M. E. Francis, and R. J. Booth, "Linguistic inquiry and word count: Liwc 2001," Mahway: Lawrence Erlbaum Associates, vol. 71, pp. 1-11, 2001.
20. C. Strapparava, A. Valitutti, et al., "Wordnet affect: an affective extension of wordnet.," in LREC, vol. 4, pp. 1083-1086, 2004.
21. B. Liu, "Sentiment analysis and opinion mining," Synthesis Lectures on Human Language Technologies, vol. 5, no. 1, pp. 1-167, 2012.