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Using Interactive Storytelling to Identify Personality Traits

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

Abstract

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.

Keywords

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

Notes

Acknowledgments

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.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Raul Paradeda
    • 1
    • 2
  • 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

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