Abstract
Dark patterns refer to tricks used in websites and apps to make you do things that you do not intend to do. This paper presents the board-game Dark Pattern, in which players install apps, draw dark patterns cards, and make choices about the sharing of personal data. To win the game, a player must share as little data as possible and play cards that punish other players. Two groups, the first with 56 students and the second with 45 students, played the game and then answered a survey with questions controlling their knowledge about the dark patterns types featured in the game. In addition, a further 50 students answered the same survey without playing the game. In this paper we present key findings about the dark patterns knowledge generated by playing the game. Then we present an exploratory analysis using Partial Least Square – Structural Equation modelling (PLS-SEM). We analysed whether dark patterns knowledge and risk perception, the likelihood of negative incidents due to data sharing, could predict the players behavioural intention to take proactive privacy steps. The two PLS-SEM models have a variance explained (R2) of 0.34 and 0.35 indicating that approximately 35% of the variance could be accounted for by the two variables included in the model. Taken together, the analyses indicated that playing the Dark Pattern game had a positive effect on behavioural intention to proactive privacy steps as a result of by playing the game.
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References
Acquisti, A., Brandimarte, L., Loewenstein, G.: Privacy and human behavior in the age of information. Science 347(6221), 509–514 (2015)
Acquisti, A., et al.: Nudges for privacy and security: understanding and assisting users’ choices online. ACM Comput. Surv. 50(3), 44 (2017)
Brignull, H., Miquel, M., Rosenberg, J., Offer, J.: Dark Patterns - User Interfaces Designed to Trick People (2015). http://darkpatterns.org/
Hartzog, W.: Privacy’s Blueprint: The Battle to Control the Design of New Technologies, p. 2018. Harvard University Press, Cambridge, MA (2018)
Mathur, A., et al.: Dark patterns at scale: findings from a Crawl of 11K shopping websites. Proc. ACM Hum.-Comput. Interact. 3(CSCW), 1–32 (2019)
Luguri, J., Strahilevitz, L.: Shining a Light on Dark Patterns. U of Chicago, Public Law Working Paper 719 (2019)
Nyvoll, K.M.: Serious Interactive Board Games: Increasing Awareness of Dark Patterns in Teenagers, Master’s thesis, Department of Computer Science at the Norwegian University of Science and Technology (NTNU) (2020)
Sarstedt, M., Ringle, C.M., Cheah, J.-H., Ting, H., Moisescu, O.I. Radomir, L.: Structural model robustness checks in PLS-SEM. Tour. Econo. 26(4), 1–24 (2019). https://doi.org/10.1177/135481661882392
Henseler, J., Ringle, C.M., Sinkovics, R.R.: The use of partial least squares path modeling in international marketing. Adv. Int. Mark. 20, 277–320 (2009)
Barclay, D.C., Higgins, C., Thompson, R.: The partial least squares approach to causal modeling: personal computer adoption and use as an illustration. Technol. Stud. 2(2), 285–308 (1995)
Chin, W.W., Marcolin, B.L., Newsted, P.R.: A partial least squares latent variables modeling approach for measuring interaction effects: results from a Monte Carlo Simulation study and an electronic-mail emotion/adoption study. Inf. Syst. Res. 14(2), 189–217 (2003)
Bagozzi, R.P., Yi, Y.: On the evaluation of structural equation models. J. Acad. Mark. Sci. 16(1), 74–94 (1988)
Gefen, D., Straub, D.: A practical guide to factorial validity using PLS-Graph: tutorial and annotated example. Commun. AIS 16(5), 91–109 (2005)
Fornell, C., Larcker, D.F.: Evaluating structural equation models with unobservable variables and measurement error. J. Mark. Res. 18(1), 39–50 (1981)
Chin, W.W.: The partial least squares approach to structural equation modeling. In: Marcoulides, G.A. (ed.) Modern methods for business research, pp. 295–358. Lawrence Erlbaum Associates, Mahwah NJ (1998)
Bellotti, F., Kapralos, B., Lee, K., Moreno-Ger, P., Berta, R.: Assessment in and of serious games: an overview. Adv. Hum.-Comput. Interact. 2013(1), 136864 (2013)
Zhonggen, Y.: A Meta-analysis of use of serious games in education over a decade. Int. J. Comput. Games Technol. 5(1), 1–8 (2019)
Tjostheim, I., Ayres Pereira, V., Wales, C., Egenfeldt-Nielsen, S., Manna, A.: Dark pattern: a serious game for learning about the dangers of sharing data. In: Proceedings of the European Conference on Games Based Learning (ECGBL 2022), vol. 16, pp. 774–783 (2022). https://doi.org/10.34190/ecgbl.16.1.872
Tjostheim, I.: A serious game about apps, data-sharing and deceptive design. In: Guarda, T., Portela, F., Diaz-Nafria, J.M. (eds.) ARTIIS 2023. CCIS, vol. 1936, pp. 332–343. Springer, Cham (2024). https://doi.org/10.1007/978-3-031-48855-9_25
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Tjostheim, I., Wales, C., Waterworth, J.A. (2024). Uncovering Dark Patterns - Learning Through Serious Gameplay About the Dangers of Sharing Data. In: Rocha, A., Adeli, H., Dzemyda, G., Moreira, F., Colla, V. (eds) Information Systems and Technologies. WorldCIST 2023. Lecture Notes in Networks and Systems, vol 800. Springer, Cham. https://doi.org/10.1007/978-3-031-45645-9_45
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DOI: https://doi.org/10.1007/978-3-031-45645-9_45
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