References
- Attardo, S. (2002). Humor and irony in interaction: From mode adoption to failure of detection. In L. Anolli, R. Ciceri, & G. Rive (Eds.), Say not to say: New perspectives on miscommunication (pp. 159–180). IOS Press.
- Bamman, D., & Smith, N. A. (2015). Contextualized sarcasm detection on Twitter. Proceedings of the Ninth International AAAI Conference on Web and social media, April 2015.
- Barbieri, F., Saigon, H., & Ronzano, F. (2014). Modelling sarcasm in Twitter, a novel approach. Proceedings of the fifth Workshop on Computational Approaches to Subjectivity, sentiment and social media analysis, June 2014.
- Boxman-Shabtai, L., & Shifman, L. (2014). Evasive targets: Deciphering polysemy in mediated humor. Journal of Communication, 64(5), 977–998. https://doi.org/https://doi.org/10.1111/jcom.12116
- boyd, d. m. (2014). It’s complicated: The social lives of networked teens. Yale University Press.
- boyd, d., & Marwick, A. (2011, May). Social steganography: Privacy in networked publics. Paper presented at The International Communication Association, Boston, MA. https://www.danah.org/papers/2011/Steganography-ICAVersion.pdf
- Caravalho, P., Sarmento, L., Silva, M. J., & de Oliviera, E. (2009). Cues for detecting irony in user-generated contents: oh … ! It’s so easy;-). Proceedings of the 1st international CIKM workshop on topic-sentiment analysis for mass option, November 2009.
- Clark, H. H., & Gerrig, R. J. (1984). On the pretense theory of irony. Journal of Experimental Psychology: General, 113(1), 121–126. https://doi.org/https://doi.org/10.1037/0096-3445.113.1.121
- Day, A. (2011). Satire and dissent. Indiana University Press.
- Dynel, M. (2014). Isn’t it ironic? Defining the scope of humorous irony. International Journal of Humor Research, 27, 619–639. https://doi.org/https://doi.org/10.1515/humor-2014-0096.
- Friedman, S., & Kuipers, G. (2013). The divisive power of humour: Comedy, taste and symbolic boundaries. Cultural Sociology, 7(2), 179–195. https://doi.org/https://doi.org/10.1177/1749975513477405
- Gal, N. (2019). Ironic humor on social media as participatory boundary work. New Media & Society, 21(3), 729–749. https://journals.sagepub.com/doi/abs/10. 1177/1461444818805719 doi: https://doi.org/10.1177/1461444818805719
- Garfinkel, H. (1956). Conditions of successful degradation ceremonies. American Journal of Sociology, 61(5), 420–424. https://doi.org/https://doi.org/10.1086/221800
- Grice, H. P. (1975). Logic and conversation. In P. Cole & J. Morgan (Eds.), Syntax and semantics, 3: Speech acts (pp. 41–58). Academic Press.
- Hernández Farias, D. I., Patti, V., & Rosso, P. (2016). Irony detection in Twitter: The role of affective content. ACM Transactions on Internet Technologies, 16(3), 1–24. doi:https://doi.org/10.1145/2930663.
- Hirsch, G., & Blum-Kulka, S. (2014). Identifying irony in news interviews. Journal of Pragmatics, 70, 31–51. https://doi.org/https://doi.org/10.1016/j.pragma.2014.06.002
- Hutcheon, L. (1994). Irony’s edge: The theory and politics of irony. Routledge.
- John, Nicholas, A., & Gal, N. (2018). “He’s Got His Own Sea”: Political Facebook Unfriending in the Personal Public Sphere. International Journal of Communication, 12(18), 2971–2988. https://ijoc.org/index.php/ijoc/article/view/8673/2410
- Joshi, A., Bhattacharrya, P., & Carman, J. M. (2017). Automatic sarcasm detection: A survey. ACM Computing Surveys, 50(5), 1–22. https://doi.org/https://doi.org/10.1145/3124420
- Joshi, A., Sharma, V., & Bhattacharyya, P. (2015). Harnessing context incongruity for sarcasm detection. Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International joint Conference on natural language Processing of Asian Federation of natural language Processing, July 2015. Association for Computational Linguistics.
- Karoui, J., Zitoune, F. B., Moriceanu, V., Aussenac-Gilles, N., & Belguith, L. H. (2015). Towards a contextual pragmatic model to detect irony in tweets. Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International joint Conference on natural language Processing of Asian Federation of natural language Processing, July 2015. Association for Computational Linguistics.
- Kotthoff, H. (2003). Responding to irony in different contexts: On cognition in conversation. Journal of Pragmatics, 35(9), 1387–1411. https://doi.org/https://doi.org/10.1016/S0378-2166(02)00182-0
- Mauchand, M., Vergis, N., & Pell, M. D. (2020). Irony, prosody, and social impressions of affective stance. Discourse Processes, 57(2), 141–157. https://doi.org/https://doi.org/10.1080/0163853X.2019.1581588.
- Meucke, D. C. (1978). Irony markers. Poetics, 7(4), 363–375. https://doi.org/https://doi.org/10.1016/0304-422X(78)90011-6
- Morreall, J. (2009). Comic relief: A comprehensive philosophy of humor. Wiley-Blackwell.
- Reyes, A., & Rosso, P. (2014). On the difficulty of automatically detecting irony: Beyond a simple case of negation. Knowledge and Information Systems, 40(3), 595–614. https://doi.org/https://doi.org/10.1007/s10115-013-0652-8
- Reyes, A., Rosso, P., & Buscaldi, D. (2012). From humor recognition to irony detection: The figurative language of social media. Data & Knowledge Engineering, 74, 1–12. https://doi.org/https://doi.org/10.1016/j.datak.2012.02.005
- Reyes, A., Rosso, P., & Veale, T. (2013). A multidimensional approach for detecting irony in Twitter. Language Resources and Evaluation, 47(1), 239–268. https://doi.org/https://doi.org/10.1007/s10579-012-9196-x
- Riloff, E., Qadir, A., Surve, P., De Silva, L., Gilbert, N., & Huang, R. (2013). Sarcasm as contrast between a positive sentiment and negative situation. Proceedings of the 2013 Conference on Empirical methods in natural language Processing, October 2013. Association for Computational Linguistics.
- Sulis, E., Hernández Farias, D. I., Rosso, P., Patti, V., & Ruffo, G. (2016). Figurative messages and affect in Twitter: Differences between #irony #sarcasm and #not. Knowledge-Based System, 108, 132–143. https://doi.org/https://doi.org/10.1016/j.knosys.2016.05.035
- Van Hee, C., Lafever, E., & Hoste, V. (2018). Exploring the fine-grained analysis and automatic detection of irony on Twitter. Language Resources and Evaluation, 52(3), 707–731. https://doi.org/https://doi.org/10.1007/s10579-018-9414-2
- Weizman, E., & Dascal, M. (1991). On clues and cues: Strategies of text-understanding. Journal of Literary Semantics, 20(1), 18–30. https://doi.org/https://doi.org/10.1515/jlse.1991.20.1.18
- Wilson, D., & Sperber, D. (1992). On verbal irony. Lingua. International Review of General Linguistics. Revue internationale De Linguistique Generale, 87(1–2), 53–76. https://doi.org/https://doi.org/10.1016/0024-3841(92)90025-E
- Zhang, S., Zhang, X., Chan, J., & Rosso, P. (2019). Irony detection via sentiment-based transfer learning. Information Processing & Management, 56(5), 1633–1644. https://doi.org/https://doi.org/10.1016/j.ipm.2019.04.006