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Your Favorite Gameplay Speaks Volumes About You: Predicting User Behavior and Hexad Type

  • Conference paper
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HCI in Games (HCII 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14047))

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Abstract

In recent years, the gamification research community has widely and frequently questioned the effectiveness of one-size-fits-all gamification schemes. In consequence, personalization seems to be an important part of any successful gamification design. Personalization can be improved by understanding user behavior and Hexad player/user type. This paper comes with an original research idea: It investigates whether users’ game-related data (collected via various gamer-archetype surveys) can be used to predict their behavioral characteristics and Hexad user types in non-game (but gamified) contexts. The affinity that exists between the concepts of gamification and gaming provided us with the impetus for running this exploratory research.

We conducted an initial survey study with 67 Stack Exchange users (as a case study). We discovered that users’ gameplay information could reveal valuable and helpful information about their behavioral characteristics and Hexad user types in a non-gaming (but gamified) environment.

The results of testing three gamer archetypes (i.e., Bartle, Big Five, and BrainHex) show that they can all help predict users’ most dominant Stack Exchange behavioral characteristics and Hexad user type better than a random labeler’s baseline. That said, of all the gamer archetypes analyzed in this paper, BrainHex performs the best. In the end, we introduce a research agenda for future work.

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Notes

  1. 1.

    More information can be found in the Section of Literature Review.

  2. 2.

    In this text, the terms typology, archetype, model, and behavioral traits are sometimes used interchangeably.

  3. 3.

    http://matthewbarr.co.uk/bartle/.

  4. 4.

    Also called Five-Factor Model of Personality.

  5. 5.

    Also called Openness to Experience.

  6. 6.

    Two moderators from Stack Exchange assisted us throughout the recruitment process.

  7. 7.

    This measure allows us to avoid studying the behavior of churned users [20].

  8. 8.

    i.e., 3/7 on the Likert scale, where 7/7 points out the maximum engagement.

  9. 9.

    Again, 7/7 shows the maximum engagement.

  10. 10.

    https://data.stackexchange.com/.

  11. 11.

    The difference between the number of up-votes and down-votes.

References

  1. Altmeyer, M., Lessel, P., Schubhan, M., Krüger, A.: Towards predicting hexad user types from smartphone data. In: Extended Abstracts of the Annual Symposium on Computer-Human Interaction in Play Companion Extended Abstracts, pp. 315–322. CHI PLAY 2019 Extended Abstracts, Association for Computing Machinery, New York, NY, USA (2019). https://doi.org/10.1145/3341215.3356266

  2. Altmeyer, M., Tondello, G.F., Krüger, A., Nacke, L.E.: Hexarcade: predicting hexad user types by using gameful applications. In: Proceedings of the Annual Symposium on Computer-Human Interaction in Play, pp. 219–230. CHI PLAY 2020, Association for Computing Machinery, New York, NY, USA (2020). https://doi.org/10.1145/3410404.3414232

  3. Anderson, A., Huttenlocher, D., Kleinberg, J., Leskovec, J.: Steering user behavior with badges. In: Proceedings of the 22nd International Conference on World Wide Web, pp. 95–106. WWW 2013, Association for Computing Machinery, New York, NY, USA (2013). https://doi.org/10.1145/2488388.2488398

  4. Barr, M., Copeland-Stewart, A.: Playing video games during the COVID-19 pandemic and effects on players’ well-being. Games Culture 17(1), 122–139 (2021). https://doi.org/10.1177/15554120211017036

  5. Bartle, R.: Hearts, clubs, diamonds, spades: players who suit muds. J. MUD Res. 1(1), 19 (1996)

    Google Scholar 

  6. Bateman, C., Lowenhaupt, R., Nacke, L.E., et al.: Player typology in theory and practice. In: DiGRA Conference, pp. 1–24. Citeseer (2011)

    Google Scholar 

  7. Boggio, C., Moscarola, F.C., Gallice, A.: What is good for the goose is good for the gander? Econ. Educ. Rev. 75, 101952 (2020) https://doi.org/10.1016/j.econedurev.2019.101952

  8. Cairns, P., Power, C., Barlet, M., Haynes, G.: Future design of accessibility in games: a design vocabulary. Int. J. Hum.-Comput. Stud. 131, 64–71 (2019). https://doi.org/10.1016/j.ijhcs.2019.06.010

  9. Chesham, A., Wyss, P., Müri, R.M., Mosimann, U.P., Nef, T.: What older people like to play: Genre preferences and acceptance of casual games. JMIR Serious Games 5(2), e8 (2017). https://doi.org/10.2196/games.7025

  10. Cole, H., Griffiths, M.D.: Social interactions in massively multiplayer online role-playing gamers. CyberPsychology Behav. 10(4), 575–583 (2007). https://doi.org/10.1089/cpb.2007.9988

  11. Connolly, T.M., Boyle, E.A., MacArthur, E., Hainey, T., Boyle, J.M.: A systematic literature review of empirical evidence on computer games and serious games. Comput. Educ. 59(2), 661–686 (2012). https://doi.org/10.1016/j.compedu.2012.03.004

  12. Deterding, S., Dixon, D., Khaled, R., Nacke, L.: From game design elements to gamefulness: defining “gamification”. In: Proceedings of the 15th International Academic MindTrek Conference: Envisioning Future Media Environments, pp. 9–15. MindTrek 2011, Association for Computing Machinery, New York, NY, USA (2011). https://doi.org/10.1145/2181037.2181040

  13. (ESA), T.E.S.A.: Essential facts about the video game industry, November 2022. https://www.theesa.com/resource/2022-essential-facts-about-the-video-game-industry/

  14. Galleguillos, L., Santelices, I., Bustos, R.: Designing a board game for industrial engineering students. a collaborative work experience of freshmen. In: INTED2019 Proceedings. IATED, March 2019. https://doi.org/10.21125/inted.2019.0075

  15. Gosling, S.D., Rentfrow, P.J., Swann, W.B.: A very brief measure of the big-five personality domains. J. Res. Pers. 37(6), 504–528 (2003). https://doi.org/10.1016/s0092-6566(03)00046-1

  16. Granic, I., Lobel, A., Engels, R.C.M.E.: The benefits of playing video games. Am. Psychol. 69(1), 66–78 (2014). https://doi.org/10.1037/a0034857

  17. Grice, J.W., Doorey, M., Lotha, G.: Five-factor model of personality, January 2019. https://www.britannica.com/science/five-factor-model-of-personality

  18. Haberlin, K.A., Atkin, D.J.: Mobile gaming and internet addiction: when is playing no longer just fun and games? Comput. Hum. Behav. 126, 106989 (2022). https://doi.org/10.1016/j.chb.2021.106989

  19. Hadi Mogavi, R., Guo, B., Zhang, Y., Haq, E.U., Hui, P., Ma, X.: When gamification spoils your learning: a qualitative case study of gamification misuse in a language-learning app. In: Proceedings of the Ninth ACM Conference on Learning @ Scale, L@S 2022, pp. 175–188. Association for Computing Machinery, New York, NY, USA (2022). https://doi.org/10.1145/3491140.3528274

  20. Hadi Mogavi, R., Haq, E.U., Gujar, S., Hui, P., Ma, X.: More gamification is not always better: a case study of promotional gamification in a question answering website. Proc. ACM Hum.-Comput. Interact. 6(CSCW2) (2022). https://doi.org/10.1145/3555553

  21. Hadi Mogavi, R., Ma, X., Hui, P.: Characterizing student engagement moods for dropout prediction in question pool websites. Proc. ACM Hum.-Comput. Interact. 5(CSCW1) (2021). https://doi.org/10.1145/3449086

  22. Hadi Mogavi, R., Zhang, Y., Haq, E.U., Wu, Y., Hui, P., Ma, X.: What do users think of promotional gamification schemes? a qualitative case study in a question answering website. Proc. ACM Hum.-Comput. Interact. 6(CSCW2) (2022). https://doi.org/10.1145/3555124

  23. Hallifax, S., Serna, A., Marty, J.C., Lavoué, G., Lavoué, E.: Factors to consider for tailored gamification. In: Proceedings of the Annual Symposium on Computer-Human Interaction in Play. p. 559–572. CHI PLAY ’19, Association for Computing Machinery, New York, NY, USA (2019). https://doi.org/10.1145/3311350.3347167,https://doi.org/10.1145/3311350.3347167

  24. Hamari, J., Koivisto, J., Sarsa, H.: Does gamification work? - a literature review of empirical studies on gamification. In: 2014 47th Hawaii International Conference on System Sciences. IEEE (2014). https://doi.org/10.1109/hicss.2014.377

  25. Hamari, J., Tuunanen, J.: Player types: A meta-synthesis (2014)

    Google Scholar 

  26. de Hesselle, L.C., Rozgonjuk, D., Sindermann, C., Pontes, H.M., Montag, C.: The associations between big five personality traits, gaming motives, and self-reported time spent gaming. Personality Individ. Differ. 171, 110483 (2021). https://doi.org/10.1016/j.paid.2020.110483

  27. Kimpen, R., De Croon, R., Vanden Abeele, V., Verbert, K.: Towards predicting hexad user types from mobile banking data: an expert consensus study. In: Extended Abstracts of the 2021 Annual Symposium on Computer-Human Interaction in Play, CHI PLAY 2021, pp. 30–36. Association for Computing Machinery, New York, NY, USA (2021). https://doi.org/10.1145/3450337.3483486

  28. Kumar, N., et al.: A chronology of sigchi conferences: 1983 to 2022. Interact. 29(6), 34–41 (2022). https://doi.org/10.1145/3568732

  29. Kusmierczyk, T., Gomez-Rodriguez, M.: On the causal effect of badges. In: Proceedings of the 2018 World Wide Web Conference, pp. 659–668. WWW 2018, International World Wide Web Conferences Steering Committee, Republic and Canton of Geneva, CHE (2018). https://doi.org/10.1145/3178876.3186147

  30. Lee, L.H., et al.: All one needs to know about metaverse: a complete survey on technological singularity, virtual ecosystem, and research agenda (2021). https://arxiv.org/abs/2110.05352

  31. Legaki, N.Z., Xi, N., Hamari, J., Karpouzis, K., Assimakopoulos, V.: The effect of challenge-based gamification on learning: an experiment in the context of statistics education. Int. J. Hum.-Comput. Stud. 144, 102496 (2020) https://doi.org/10.1016/j.ijhcs.2020.102496

  32. Lopez, C.E., Tucker, C.S.: The effects of player type on performance: a gamification case study. Comput. Hum. Behav. 91, 333–345 (2019). https://doi.org/10.1016/j.chb.2018.10.005

  33. Ltd, I.H.: Brainhex questionnaire, May 2010. https://survey.ihobo.com/BrainHex/

  34. Mogavi, R.H., Gujar, S., Ma, X., Hui, P.: Hrcr: hidden markov-based reinforcement to reduce churn in question answering forums. In: Pacific Rim International Conference on Artificial Intelligence, pp. 364–376 (2019)

    Google Scholar 

  35. Nacke, L.E., Bateman, C., Mandryk, R.L.: BrainHex: a neurobiological gamer typology survey. Entertainment Comput. 5(1), 55–62 (2014). https://doi.org/10.1016/j.entcom.2013.06.002

  36. Nicholson, S.: A recipe for meaningful gamification. Gamification in education and business, pp. 1–20 (2015)

    Google Scholar 

  37. Orji, R., Mandryk, R.L., Vassileva, J., Gerling, K.M.: Tailoring persuasive health games to gamer type. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI 2013, pp. 2467–2476. Association for Computing Machinery, New York, NY, USA (2013). https://doi.org/10.1145/2470654.2481341

  38. Orji, R., Nacke, L.E., Marco, C.D.: Towards personality-driven persuasive health games and gamified systems. In: Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, ACM, May 2017. https://doi.org/10.1145/3025453.3025577

  39. Orji, R., Tondello, G.F., Nacke, L.E.: Personalizing persuasive strategies in gameful systems to gamification user types. In: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, CHI 2018, pp. 1–14. Association for Computing Machinery, New York, NY, USA (2018). https://doi.org/10.1145/3173574.3174009

  40. Parry, I., Carbullido, C., Kawada, J., Bagley, A., Sen, S., Greenhalgh, D., Palmieri, T.: Keeping up with video game technology: objective analysis of xbox kinect™ and PlayStation 3 move™ for use in burn rehabilitation. Burns 40(5), 852–859 (2014). https://doi.org/10.1016/j.burns.2013.11.005

  41. Reiners, T., Wood, L.C. (eds.): Gamification in Education and Business. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-10208-5

    Book  Google Scholar 

  42. Ryan, R.M., Rigby, C.S., Przybylski, A.: The motivational pull of video games: a self-determination theory approach. Motiv. Emot. 30(4), 344–360 (2006). https://doi.org/10.1007/s11031-006-9051-8

  43. Seaborn, K., Fels, D.I.: Gamification in theory and action: a survey. Int. J. Hum.-Comput. Stud. 74, 14–31 (2015). https://doi.org/10.1016/j.ijhcs.2014.09.006

  44. Srba, I., Bielikova, M.: A comprehensive survey and classification of approaches for community question answering. ACM Trans. Web 10(3) (2016). https://doi.org/10.1145/2934687

  45. Thayer, A., Kolko, B.E.: Localization of digital games: the process of blending for the global games market. Tech. Commun. 51(4), 477–488 (2004)

    Google Scholar 

  46. Tondello, G.F., Arrambide, K., Ribeiro, G., Cen, A.J., Nacke, L.E.: “I don’t fit into a single type: a trait model and scale of game playing preferences. In: Lamas, D., Loizides, F., Nacke, L., Petrie, H., Winckler, M., Zaphiris, P. (eds.) INTERACT 2019. LNCS, vol. 11747, pp. 375–395. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-29384-0_23

    Chapter  Google Scholar 

  47. Tondello, G.F., Wehbe, R.R., Diamond, L., Busch, M., Marczewski, A., Nacke, L.E.: The gamification user types hexad scale. In: Proceedings of the 2016 Annual Symposium on Computer-Human Interaction in Play, CHI PLAY 2016, pp. 229–243. Association for Computing Machinery, New York, NY, USA (2016). https://doi.org/10.1145/2967934.2968082

  48. Troiano, G.M., et al.: Exploring how game genre in student-designed games influences computational thinking development. In: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, CHI 2020, pp. 1–17. Association for Computing Machinery, New York, NY, USA (2020). https://doi.org/10.1145/3313831.3376755

  49. Tyack, A., Mekler, E.D.: Self-determination theory in HCI games research: current uses and open questions. In: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, CHI 2020, pp. 1–22. Association for Computing Machinery, New York, NY, USA (2020). https://doi.org/10.1145/3313831.3376723

  50. Urbanek, M., Güldenpfennig, F.: Unpacking the audio game experience: lessons learned from game veterans. In: Proceedings of the Annual Symposium on Computer-Human Interaction in Play, CHI PLAY 2019, pp. 253–264. Association for Computing Machinery, New York, NY, USA (2019). https://doi.org/10.1145/3311350.3347182

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Acknowledgement

The authors would like to thank Mr. Rahman Hadi Mogavi for proofreading and contributing beautiful images to this paper. This research has been supported in part by the MetaHKUST project from the Hong Kong University of Science and Technology (Guangzhou), and 5GEAR and FIT projects from the Academy of Finland.

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Authors and Affiliations

  1. Hong Kong University of Science and Technology, Hong Kong Sar, China

    Reza Hadi Mogavi, Ehsan-Ul Haq & Pan Hui

  2. Accessible Meta Research and Development, Michigan, USA

    Chao Deng & Jennifer Hoffman

  3. International Institute of Information Technology, Hyderabad, India

    Sujit Gujar

  4. Fondazione Bruno Kessler, Trento, Italy

    Antonio Bucchiarone

  5. Hong Kong University of Science and Technology, Guangzhou, China

    Pan Hui

  6. University of Helsinki, Helsinki, Finland

    Pan Hui

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  1. Reza Hadi Mogavi
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  2. Chao Deng
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Correspondence to Reza Hadi Mogavi .

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  1. DePaul University, Chicago, IL, USA

    Xiaowen Fang

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Hadi Mogavi, R. et al. (2023). Your Favorite Gameplay Speaks Volumes About You: Predicting User Behavior and Hexad Type. In: Fang, X. (eds) HCI in Games. HCII 2023. Lecture Notes in Computer Science, vol 14047. Springer, Cham. https://doi.org/10.1007/978-3-031-35979-8_17

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  • DOI: https://doi.org/10.1007/978-3-031-35979-8_17

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