Abstract
Writing style is considered the manner how an author expresses his thoughts, influenced by language characteristics of an individual, period, school, or nation. Most of the times, this writing style can identify the author. Yet, one of the most famous examples comes from 1914 in Portuguese literature, with Fernando Pessoa and his heteronyms Alberto Caeiro, Álvaro de Campos and Ricardo Reis, who had completely different writing styles and led people to believe that they were different individuals. So, the discussion about authorship identification already exists along a century. Currently, there are several alternatives to identify authors of text, however, these solutions do not consider the emotion contained in the text as source of information in the writing style.
This paper is about a process to analyse the emotion contained in social media messages as Facebook (http://www.facebook.com) in order to identify the author’s emotional profile and use it to improve the ability to predict the authors of the messages. Using preprocessing techniques, lexicon-based approaches and machine learning, we achieved an authorship identification improvement around 5% in the whole dataset and more than 50% in specific authors, when considering the emotional profile on the writing style.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Baldoni, M., Baroglio, C., Patti, V., Rena, P.: From tags to emotions: ontology-driven sentiment analysis in the social semantic web. Intelligenza Artificiale 6(1), 41–54 (2012)
Cambria, E., Hussain, A., Havasi, C., Eckl, C.: SenticSpace: visualizing opinions and sentiments in a multi-dimensional vector space. In: KES (4), pp. 385–393. Springer (2010)
Ekman, P.: An argument for basic emotions. Cogn. Emot. 6(3–4), 169–200 (1992)
Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., Witten, I.H.: The WEKA data mining software: an update. ACM SIGKDD Explor. Newsl. 11(1), 10–18 (2009)
Leventhal, H., Scherer, K.: The relationship of emotion to cognition: a functional approach to a semantic controversy. Cogn. Emot. 1(1), 3–28 (1987)
Manning, C.D., Surdeanu, M., Bauer, J., Finkel, J., Bethard, S.J., McClosky, D.: The Stanford CoreNLP natural language processing toolkit. In: Association for Computational Linguistics (ACL) System Demonstrations, pp. 55–60 (2014)
Mohammad, S.M., Turney, P.D.: Crowdsourcing a word-emotion association lexicon. Comput. Intell. 29(3), 436–465 (2013)
Plutchik, R.: Emotions: a general psychoevolutionary theory. Approaches to Emotion 1984, 197–219 (1984)
Scherer, K.R., Dalgleish, T., Power, M.: Handbook of cognition and emotion. In: Handbook of Cognition and Emotion (1999)
Schwartz, H.A., Sap, M., Kern, M.L., Eichstaedt, J.C., Kapelner, A., Agrawal, M., Blanco, E., Dziurzynski, L., Park, G., Stillwell, D., et al.: Predicting individual well-being through the language of social media. In: Biocomputing 2016: Proceedings of the Pacific Symposium, pp. 516–527 (2016)
Zheng, R., Li, J., Chen, H., Huang, Z.: A framework for authorship identification of online messages: writing-style features and classification techniques. J. Assoc. Inf. Sci. Technol. 57(3), 378–393 (2006)
Acknowledgements
This work has been supported by COMPETE: POCI-01-0145-FEDER-0070 43 and FCT – Fundação para a Ciência e Tecnologia within the Project Scope UID/CEC/ 00319/2013.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG, part of Springer Nature
About this paper
Cite this paper
Martins, R., Almeida, J., Henriques, P., Novais, P. (2018). Increasing Authorship Identification Through Emotional Analysis. In: Rocha, Á., Adeli, H., Reis, L.P., Costanzo, S. (eds) Trends and Advances in Information Systems and Technologies. WorldCIST'18 2018. Advances in Intelligent Systems and Computing, vol 745. Springer, Cham. https://doi.org/10.1007/978-3-319-77703-0_76
Download citation
DOI: https://doi.org/10.1007/978-3-319-77703-0_76
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-77702-3
Online ISBN: 978-3-319-77703-0
eBook Packages: EngineeringEngineering (R0)