Using Interactive Storytelling to Identify Personality Traits

  • Raul ParadedaEmail author
  • Maria José Ferreira
  • Carlos Martinho
  • Ana Paiva
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10690)


Each person feels and understands stories in a unique way. Stories have different meanings to people, and those depend on their personal experiences and personality. Each one of us is unique, with unique personality traits, classifiable through personality trait theories, such as the Myers-Briggs theory. In this paper, we describe how we have created a database of 155 individuals to extract their personality classifications based on Myers-Briggs Type Indicator and then used the fact that each person’s individual traits impact the interpretation of interactive storytelling. With this work, we intend to perceive transparently (i.e. without questionnaire and using the language of the interactive experience itself) the person’s personality in order to create through the use of persuasion a personalised narrative experience. Through a concrete study, we show how an Interactive Storytelling scenario can be used to identify users personality traits. In particular, by extracting the decisions taken by a user in an interactive storytelling scenario, we are able to predict the user’s MBTI personality traits.


Interactive storytelling Personality traits Myers-briggs type indicator Decision points Preferences 



We would like to thank Professor Isabel Benites who aided in the story creation, the National Council for Scientific and Technological Development (CNPq) program Science without Border: 201833/2014-0 - Brazil and Agência Regional para o Desenvolvimento e Tecnologia (ARDITI) - M1420-09-5369-000001, for PhD grants to first and second authors respectively. This work was also supported by Fundação para a Ciência e a Tecnologia: (FCT) - UID/CEC/50021/2013 and the project AMIGOS:PTDC/EEISII/7174/2014.


  1. 1.
    Birk, M.V., Toker, D., Mandryk, R.L., Conati, C.: Modeling motivation in a social network game using player-centric traits and personality traits. In: Ricci, F., Bontcheva, K., Conlan, O., Lawless, S. (eds.) UMAP 2015. LNCS, vol. 9146, pp. 18–30. Springer, Cham (2015). CrossRefGoogle Scholar
  2. 2.
    Figueiredo, R., Paiva, A.: Affecting choices in interactive storytelling. In: AAAI Fall Symposium: Computational Models of Narrative (2010)Google Scholar
  3. 3.
    Jung, C., Adler, G., Hull, R.: Collected Works of C.G. Jung, Volume 6: Psychological Types. Princeton University Press, Princeton (2014)CrossRefGoogle Scholar
  4. 4.
    Kaplan, R., Saccuzzo, D.: Psychological Testing: Principles, Applications, and Issues. Cengage Learning, Boston (2012)Google Scholar
  5. 5.
    Klimmt, C., Roth, C., Vermeulen, I., Vorderer, P.: The empirical assessment of the user experience in interactive storytelling: construct validation of candidate evaluation measures. Technical report. Integrating Research in Interactive Storytelling-IRIS (2010)Google Scholar
  6. 6.
    McDonald, E.: The Global Games Market 2017 | Per Region & Segment | Newzoo (2017).
  7. 7.
    Miller, S., Pennycuff, L.: The power of story: Using storytelling to improve literacy learning. J. Cross-Discipl. Perspect. Educ. 1(1), 8 (2008)Google Scholar
  8. 8.
    Myers, I., Myers, P.: Gifts Differing: Understanding Personality Type. Davies-Black Publication, Palo Alto, California (1980)Google Scholar
  9. 9.
    Nacke, L.E., Bateman, C., Mandryk, R.L.: BrainHex: preliminary results from a neurobiological gamer typology survey. In: Anacleto, J.C., Fels, S., Graham, N., Kapralos, B., Saif El-Nasr, M., Stanley, K. (eds.) ICEC 2011. LNCS, vol. 6972, pp. 288–293. Springer, Heidelberg (2011). CrossRefGoogle Scholar
  10. 10.
    OECD: Student Learning Attitudes, Engagement and Strategies. In: Learning for Tomorrow’s World: First Results from PISA 2003, pp. 109–158. Organisation for Economic Cooperation and Development (OECD), Paris (2004)Google Scholar
  11. 11.
    Paiva, A.: The role of tangibles in interactive storytelling. In: Subsol, G. (ed.) ICVS 2005. LNCS, vol. 3805, pp. 225–228. Springer, Heidelberg (2005). CrossRefGoogle Scholar
  12. 12.
    Paradeda, R.B., Martinho, C., Paiva, A.: Persuasion based on personality traits: Using a social robot as storyteller. In: Proceedings of the Companion of the 2017 ACM/IEEE International Conference on Human-Robot Interaction, HRI 2017, NY, USA. pp. 367–368. ACM, New York (2017).
  13. 13.
    Prada, R., Santos, P., Martinho, C.: Design E Desenvolvimento De Jogos. FCA (BRASIL)Google Scholar
  14. 14.
    Ryokai, K., Vaucelle, C., Cassell, J.: Virtual peers as partners in storytelling and literacy learning. J. Comput. Assist. Learn. 19(2), 195–208 (2003)CrossRefGoogle Scholar
  15. 15.
    The Myers & Briggs Foundation: The Myers & Briggs Foundation - MBTI® Basics (2014).
  16. 16.
    Van, G.: Potential applications of digital storytelling in education. In: Paper presented at the 3rd Twente Student Conference on IT, Department of Electrical Engineering, Mathematics and Computer Science (2005)Google Scholar
  17. 17.
    Wang, C.Y.: Preference measures of rectangle ratio on MBTI personality types. Art Des. Rev. 3(03), 69 (2015)Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Raul Paradeda
    • 1
    • 2
    Email author
  • Maria José Ferreira
    • 1
    • 3
  • Carlos Martinho
    • 1
  • Ana Paiva
    • 1
  1. 1.INESC-ID and Instituto Superior TécnicoUniversity of LisbonLisbonPortugal
  2. 2.Rio Grande do Norte State UniversityNatalBrazil
  3. 3.Madeira Interactive Technologies InstituteMadeiraPortugal

Personalised recommendations