Predicting Cognitive Profiles from a Mini Quiz: A Facebook Game for Cultural Heritage

  • Angeliki AntoniouEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11385)


Games are used in cultural heritage to engage visitors, to function as learning tools, or even advertise a venue. However, games can be also used for quick profiling purposes to overcome the cold start problem of personalized museum applications. A profiling game aiming to extract users’ cognitive profiles was developed and tested with real users. The game follows the principles of pop psychology quizzes. The results of the game showed its potential in correctly predicting the cognitive profiles of users with average success rate around 90%. Being an entertaining and engaging way to involve visitors with diverse needs, games and especially profiling have a clear place in cultural heritage and should be investigated further. Our future work will focus on games that will try to predict different personality aspects, like Big Five dimensions.


Games Cultural heritage Profiling Cognitive profiles 



This work is supported by CrossCult: “Empowering reuse of digital cultural heritage in context-aware crosscuts of European history”, funded by the European Union’s Horizon 2020 research and innovation program, Grant# 693150. I would also like to thank Ms Bampatzia for game implementation and Ms Maipa for data collection.


  1. 1.
    Bellotti, F., Berta, R., De Gloria, A., D’ursi, A., Fiore, V.: A serious game model for cultural heritage. J. Comput. Cult. Herit. 5(4, Article 17), 27 pages (2013). Scholar
  2. 2.
    Mortara, M., Catalano, C.E., Bellotti, F., Fiucci, G., Houry-Panchetti, M., Petridis, P.: Learning cultural heritage by serious games. J. Cult. Herit. 15(3), 318–325 (2014)CrossRefGoogle Scholar
  3. 3.
    Coenen, T., Mostmans, L., Naessens, K.: MuseUs: case study of a pervasive cultural heritage serious game. J. Comput. Cult. Herit. 6(2, Article 8), 19 pages (2013). Scholar
  4. 4.
    Ardissono, L., Kuflik, T., Petrelli, D.: Personalization in cultural heritage: the road travelled and the one ahead. User Model. User-Adap. Inter. 22(1–2), 73–99 (2012)CrossRefGoogle Scholar
  5. 5.
    Antoniou, A., et al.: User profiling: towards a facebook game that reveals cognitive style. In: De Gloria, A. (ed.) GALA 2013. LNCS, vol. 8605, pp. 349–353. Springer, Cham (2014). Scholar
  6. 6.
    Briggs-Myers, I., McCaulley, M.H.: Manual: A Guide to the Development and Use of the Myers-Briggs Type Indicator. Consulting Psychologists Press, Palo Alto (1985)Google Scholar
  7. 7.
    Frick, A., Bächtiger, M.T., Reips, U.D.: Dimensions of internet science (2001)Google Scholar
  8. 8.
    Reips, U.D.: Internet-based psychological experimenting: five dos and five don’ts. Soc. Sci. Comput. Rev. 20(3), 241–249 (2002)Google Scholar
  9. 9.
    Costa Jr., P.T., McCrae, R.R.: Revised NEO Personality Inventory (NEO-PI-R) and NEO Five-Factor Inventory (NEO-FFI) Manual. Psychological Assessment Resources, Odessa (1992)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.University of PeloponneseTripolisGreece

Personalised recommendations