Abstract
Author profiling deals with distinguishing between classes of authors rather than individual authors on the basis of their usage of language. What is much more subjective in terms of usage of language is when authors employ irony as linguistic device. The aim of this paper is to introduce the reader to concepts such as universality of language among classes of authors, e.g. of the same gender, and creativity in irony.
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PAN Lab on Uncovering Plagiarism, Authorship, and Social Software Misuse: http://pan.webis.de.
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EmIroGeFB: http://ow.ly/uQWEs.
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Given a set of tweets the task consist in determining whether the user has expressed a positive, negative or neutral sentiment; more information is available at: http://alt.qcri.org/semeval2015/task11/.
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We use Weka toolkit’s version of each classifier available at: http://www.cs.waikato.ac.nz/ml/weka/dowloading.html.
References
Argamon, S., Koppel, M., Fine, J., Shimoni, A.R.: Gender, genre, and writing style in formal written texts. In: TEXT, vol. 23, pp. 321–346 (2003)
Baccianella, S., Esuli, A., Sebastiani F.: SentiWordNet 3.0: an enhanced lexical resource for sentiment analysis and opinion mining. In: Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC) (2010)
Basile, V., Bolioli, A., Nissim, M., Patti, V., Rosso, P.: Overview of the Evalita 2014 SENTIment POLarity Classification Task. In: Proceeding of the 4th Evaluation Campaign of Natural Language Processing and Speech tools for Italian, EVALITA-2014, Pisa, Italy, pp. 50-57, Dec. 9-11 (2014)
Barbieri, F., Saggion, H.: 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, pp. 56-64 Association for Computational Linguistics (2014)
Barbieri, F., Saggion, H., Ronzano, F.: Modelling sarcasm in twitter, a novel approach. In: Proceedings of the 5th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, pp. 50–58. Association for Computational Linguistics (2014)
Bosco, C., Patti, V., Bolioli, A.: Developing corpora for sentiment analysis: the case of irony and Senti-TUT. IEEE Intell. Syst. 28(2), 55–63 (2013)
Bradley, M., Lang, P.: Affective Norms for English Words (ANEW): Instruction Manual and Affective Ratings (1999)
Buschmeier, K., Cimiano, P., Klinger, R.: An impact analysis of features in a classification approach to irony detection in product reviews. In: Proceedings of the 5th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, WASSA-2014, pp. 42-49. Association for Computational Linguistics (2014)
Cambria, E., Havasi, C., Hussain, A.: SenticNet 2: a semantic and affective resource for opinion mining and sentiment analysis. In: Proceedings of the FLAIRS: Florida Artificial Intelligence Research Society Conference (2012)
Díaz Rangel, I.: Detección de afectividad en texto en español basada en el contexto lingüístico para síntesis de voz. Tesis Doctoral. Instituto Politécnico Nacional. México (2013) (in Spanish)
Fleiss, Joseph L.: Measuring nominal scale agreement among many raters. Psychol. Bull. 76(5), 378–382 (1971)
Gibbs, R.W., Colston, H.L.: Irony in Language and Thought. Routledge (Taylor and Francis), New York (2007)
Ghosh, A., Li, G., Veale, T., Rosso, P., Shutova, E., Reyes, A., Barnden, J.: SemEval-2015 Task 11: sentiment analysis of figurative language in twitter. In: Proceedings International Workshop on Semantic Evaluation (SemEval-2015), Co-located with NAACL and *SEM (2015)
Goswami, S., Sarkar, S., Rustagi, M.: Stylometric analysis of bloggers’ age and gender. In: Proceedings of the Third International Conference on Weblogs and Social Media (ICWSM). AAAI Press (2009)
Hernández-Farías, I., Benedí, J.M., Rosso, P.: Applying basic features from sentiment analysis for automatic irony detection. In: Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA) 2015, Santiago de Compostela (Spain), June 17-19 (2015)
Hu, M., Liu, B.: Mining and summarizing customer reviews. In: Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (2004)
Koppel, M., Argamon, S., Shimoni, A.: Automatically categorizing written texts by author gender. Lit. Linguist. Comput. 17(4), 401–412 (2003)
Levin, B.: English Verb Classes and Alternations. University of Chicago Press, Chicago (1993)
Mohammad, S.M., Turney, P.D.: Crowdsourcing a word-emotion association lexicon. Comput. Intell. 29(3), 436–465 (2013). Wiley Online Library
Nielsen, F.: A new ANEW: Evaluation of a word list for sentiment analysis in microblogs. In: Proceedings of the Workshop on Making Sense of Microposts (2011)
Nguyen, D., Gravel, R., Trieschnigg, D., Meder, T.: How Old Do You Think I Am?; a study of language and age in twitter. In: Proceedings of the Seventh International AAAI Conference on Weblogs and Social Media (2013)
Ott, M., Choi, Y., Cardie, C., Hancock, J. T.: Finding deceptive opinion spam by any stretch of the imagination. In: Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, Portland, Oregon, USA (2011)
Pastor Lopez-Monroy, A., Montes-Gomez, M., Jair Escalante, H., Villasenor-Pineda, L., Villatoro-Tello, E.: INAOEs participation at PAN13: author profiling task. In: Notebook for PAN at CLEF (2013)
Pennebaker, J.W., Francis, M., Booth, R.: Linguistic inquiry and word count: LIWC 2001. In: Mahway, vol. 71. Lawrence Erlbaum Associates (2001)
Pennebaker, J.W., Mehl, M.R., Niederhoffer, K.: Psychological aspects of natural language use: our words, our selves. Ann. Rev. Psychol. 54, 547–577 (2003)
Pennebaker, J.W.: The Secret Life of Pronouns: What Our Words Say About Us. Bloomsbury Press, London (2011)
Rangel, F., Hernández, I., Rosso, P., Reyes, A.: Emotions and irony per gender in facebook. In: Proceedings of Workshop on Emotion, Social Signals, Sentiment & Linked Open Data (ES3LOD), LREC-2014, Reykjavík, Iceland, May 26–31 (2014)
Rangel, F., Rosso, P.: On the identification of emotions and authors’ gender in facebook comments on the basis of their writing style. In: Proceedings of ESSEM Workshop on Emotion and Sentiment in Social and Expressive Media, AIxIA, vol. 1096, pp. 34-46. http://CEUR-WS.org (2013)
Rangel, F., Rosso, P., Koppel, M., Stamatatos, E., Inches, G.: Overview of the author profiling task at PAN 2013. In: Forner P., Navigli R., Tufis D. (eds.), CLEF 2013 Labs and Workshops, Notebook Papers, vol. 1179, Valencia, Spain, Sept. 23–26. http://CEUR-WS.org (2013)
Rangel, F., Rosso, P., Chugur, I., Potthast, M., Trenkmann, M., Stein, B., Verhoeven, B., Daelemans, W.: Overview of the 2nd author profiling task at PAN 2014. In: Cappellato, L., Ferro, N., Halvey, M., Kraaij, W. (eds.) CLEF 2014 Labs and Workshops, Notebook Papers, vol. 1180, pp. 898-827. http://CEUR-WS.org (2014)
Rangel, F., Rosso, P.: On the impact of emotions on author profiling. In: Information Processing & Management 52(1), 73–92 (2016)
Rangel, F., Rosso, P.: Use of language and author profiling: identification of gender and age. In: 10th International Workshop on Natural Language Processing and Cognitive Sciences NLPCS 2013 CIRM, Marseille, France, Oct. 13–17 (2013)
Reyes, A., Rosso, P., Veale, T.: A multidimensional approach for detecting irony in twitter. Lang. Res. Eval. 47(1), 239–268 (2013)
Reyes, A., Rosso, P.: On the difficulty of automatically detecting irony: beyond a simple case of negation. Knowl. Inf. Syst. 40(3), 595–614 (2014)
Schler, J., Koppel, M., Argamon, S, Pennebaker, J.W.: Effects of age and gender on blogging. In: AAAI Spring Symposium: Computational Approaches to Analyzing Weblogs, pp. 199-205. AAAI (2006)
Stone, P.J., Hunt, E.B.: A computer approach to content analysis: studies using the general lnquirer system. In: Proceedings of the May 21–23, Spring Joint Computer Conference (1963)
Sulis, E., Hernández-Farias, I., Rosso, P., Patti, V., Ruffo, G.: Figurative messages and affect in twitter: differences between #irony, #sarcasm and #not, Knowledge-Based Systems (submitted)
Veale, T., Hao, Y.: Detecting Ironic Intent in Creative Comparisons. In: Coelho, H., Studer, R.,Wooldridge, M. (eds.), Proceedings of the 19th European Conference on Artificial Intelligence (ECAI) Frontiers in Artificial Intelligence and Applications, vol. 215, pp. 765-770. IOS Press (2010)
Wallace, B.: Computational irony: a survey and new perspectives. In: Artificial Intelligence Review, pp. 1-17. Springer Netherlands (2013)
Wang, A.P.: #Irony or #Sarcasm—a quantitative and qualitative study based on twitter. In: Proceedings of the PACLIC: the 27th Pacific Asia Conference on Language, Information, and Computation (2013)
Whissell, C.: Using the revised dictionary of affect in language to quantify the emotional undertones of samples of natural languages. In: Psychological Reports (2009)
Acknowledgments
The research work was carried out in the VLC/CAMPUS Microcluster on Multimodal Interaction in Intelligent Systems in the framework of the SomEMBED TIN2015-71147-C2-1-P MINECO research project and under the Generalitat Valenciana grant ALMAMATER (PrometeoII/2014/030). The National Council for Science and Technology (CONACyT-Mexico) has funded the research work of the second author (Grant No. 218109/313683, CVU-369616). The work of the third author was partially funded by Autoritas Consulting SA and by Ministerio de Economia de España under grant ECOPORTUNITY IPT-2012-1220-n430000.
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Rosso, P., Hernández Farías, D.I., Rangel, F. (2016). Universality and Creativity: The Usage of Language in Gender and Irony. In: Degli Esposti, M., Altmann, E., Pachet, F. (eds) Creativity and Universality in Language. Lecture Notes in Morphogenesis. Springer, Cham. https://doi.org/10.1007/978-3-319-24403-7_11
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