Increasing Authorship Identification Through Emotional Analysis
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.
KeywordsSentiment analysis Machine learning Natural processing language
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.
- 1.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)Google Scholar
- 6.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)Google Scholar
- 8.Plutchik, R.: Emotions: a general psychoevolutionary theory. Approaches to Emotion 1984, 197–219 (1984)Google Scholar
- 9.Scherer, K.R., Dalgleish, T., Power, M.: Handbook of cognition and emotion. In: Handbook of Cognition and Emotion (1999)Google Scholar
- 10.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)Google Scholar