Abstract
This paper presents computational work to detect satire/sarcasm in long commentaries on Italian politics. It uses the lexica extracted from the manual annotation based on Appraisal Theory, of some 30 K word texts. The underlying hypothesis is that using this framework it is possible to precisely pinpoint ironic content through the deep semantic analysis of evaluative judgement and appreciation. The paper presents the manual annotation phase realized on 112 texts by two well-known Italian journalists. After a first experimentation phase based on the lexica extracted from the xml output files, we proceeded to retag lexical entries dividing them up into two subclasses: figurative and literal meaning. Finally more fine-grained Appraisal features have been derived and more experiments have been carried out and compared to results obtained by a lean sentiment analysis. The final output is produced from held out texts to verify the usefulness of the lexica and the Appraisal theory in detecting ironic content.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
Notes
- 1.
Permission to republish excerpts from their articles has been granted personally by the authors.
- 2.
As reported in M&W p. 52.
References
Martin, J., White, P.R.: Language of Evaluation, Appraisal in English. Palgrave/Macmillan, London/New York (2005)
Taboada, M., Grieve, J.: Analyzing appraisal automatically. In: Proceedings of the AAAI Spring Symposium on Exploring Attitude and Affect in Text: Theories and Applications, pp. 158–161. AAAI Press (2004)
Fletcher, J., Patrick, J.: Evaluating the utility of appraisal hierarchies as a method for sentiment classification. Proceedings of the Australasian Language Technology Workshop, pp. 134–142, Sydney (2005)
Khoo, C., Nourbakhsh, A., Na, J.: Sentiment analysis of online news text: a case study of appraisal theory. Online Inf. Rev. 36(6), 858–878 (2012)
Sarmento, L., Carvalho, P., Silva, M., de Oliveira, E.: Automatic creation of a reference corpus for political opinion mining in user-generated content. In: Proceedings of the 1st international CIKM workshop on Topic-sentiment analysis for mass opinion, pp. 29–36. ACM, Hong Kong (2009)
Carvalho, P., Sarmento, L., Silva, M., de Oliveira, E.: Clues for detecting irony in user-generated contents: oh…!! it’s so easy;-). In: Proceeding of the 1st International CIKM Workshop on Topic-Sentiment Analysis for Mass Opinion, pp. 53–56. ACM, Hong Kong (2009)
Reyes, A., Rosso, P.: Mining subjective knowledge from customer reviews: a specific case of irony detection. In: WASSA 2011 Proceedings of the 2nd Workshop on Computational Approaches to Subjectivity and Sentiment Analysis, pp. 118–124. Association for Computational Linguistics, Stroudsburg (2011)
Özdemir, C., Bergler, S.: CLaC-SentiPipe: SemEval2015 Subtasks 10 B, E, and Task 11. In: Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015), pp. 479–485. Association for Computational Linguistics, Denver (2015)
Gruner, C.: The Game of Humor: A Comprehensive Theory of Why We Laugh. Transaction Publishers, New Brunswick (1997)
Freud, S.: Der Witz und seine Beziehung zum Unbewußten. Franz Deuticke, Leipzig (1905)
Minsky, M.: Jokes and their Relation to the Cognitive Unconscious. In: Vaina, L., Hintikka, J. (eds.) Cognitive Constraints on Communication: Representations and Processes. D. Reidel, Dordrecht (1981)
Koestler, A.: The Act of Creation. Hutchinson & Co, London (1964)
Raskin, V.: Semantic Mechanisms of Humor. D. Reidel, Dordrecht (1985)
Attardo, S., Raskin, V.: Script theory revis(it)ed: joke similarity. HUMOR: Int. J. Humor Res. 4(3/4), 293–347 (1991)
Attardo, S.: Linguistic Theories of Humor. Mouton de Gruyter, Berlin (1994)
Bosco, C., Patti, V., Bolioli, A.: Developing corpora for sentiment analysis: the case of irony and Senti-TUT (extended abstract). In: Yang, Q., Wooldridge, M. (eds.) Proceeding of 24th International Joint Conference on Artificial Intelligence, IJCAI 2015, pp. 4158–4162. AAAI Press, Buenos Aires (2015)
Birke, J., Sarkar, A.: Active learning for the identification of nonliteral language. In: FigLanguages 2007 Proceedings of the Workshop on Computational Approaches to Figurative Language, pp. 21–28. Omnipress Inc, Rochester (2007)
Turney, D., Neuman, Y., Assaf, D., Cohen, Y.: Literal and metaphorical sense identification through concrete and abstract context. In: EMNLP 2011 Proceedings of the Conference on Empirical Methods in Natural Language Processing, pp. 680–690. Association for Computational Linguistics, Edinburgh (2011)
Hernandez Farias, D., Sulis, E., Patti, V., Ruffo, G., Bosco, C.: ValenTo: sentiment analysis of figurative language tweets with irony and sarcasm. In: Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015), pp. 694–698. Association for Computational Linguistics, Denver (2015)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Delmonte, R., Stingo, M. (2016). Detecting Satire in Italian Political Commentaries. In: Nguyen, N., Iliadis, L., Manolopoulos, Y., Trawiński, B. (eds) Computational Collective Intelligence. ICCCI 2016. Lecture Notes in Computer Science(), vol 9876. Springer, Cham. https://doi.org/10.1007/978-3-319-45246-3_7
Download citation
DOI: https://doi.org/10.1007/978-3-319-45246-3_7
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-45245-6
Online ISBN: 978-3-319-45246-3
eBook Packages: Computer ScienceComputer Science (R0)