Increasing Authorship Identification Through Emotional Analysis

  • Ricardo Martins
  • José Almeida
  • Pedro Henriques
  • Paulo Novais
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 745)


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 ( 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.


Sentiment 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. 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
  2. 2.
    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)CrossRefGoogle Scholar
  3. 3.
    Ekman, P.: An argument for basic emotions. Cogn. Emot. 6(3–4), 169–200 (1992)CrossRefGoogle Scholar
  4. 4.
    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)CrossRefGoogle Scholar
  5. 5.
    Leventhal, H., Scherer, K.: The relationship of emotion to cognition: a functional approach to a semantic controversy. Cogn. Emot. 1(1), 3–28 (1987)CrossRefGoogle Scholar
  6. 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
  7. 7.
    Mohammad, S.M., Turney, P.D.: Crowdsourcing a word-emotion association lexicon. Comput. Intell. 29(3), 436–465 (2013)MathSciNetCrossRefGoogle Scholar
  8. 8.
    Plutchik, R.: Emotions: a general psychoevolutionary theory. Approaches to Emotion 1984, 197–219 (1984)Google Scholar
  9. 9.
    Scherer, K.R., Dalgleish, T., Power, M.: Handbook of cognition and emotion. In: Handbook of Cognition and Emotion (1999)Google Scholar
  10. 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
  11. 11.
    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)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Ricardo Martins
    • 1
  • José Almeida
    • 1
  • Pedro Henriques
    • 1
  • Paulo Novais
    • 1
  1. 1.Algoritmi Centre/Department of InformaticsUniversity of MinhoBragaPortugal

Personalised recommendations