Who are the gamers? Profiling adult gamers using machine learning approaches

Abstract

In our paper, we used factor analysis and artificial intelligence-based modeling to reveal how video gamers living in an economically peripheric European Union member state can be segmented based on gaming time. We performed a causal analysis of two groups—occasional and frequent players—based on the data of a 2022 representative survey. The results show that in a semi-peripheral country, the adult population plays video games in a similar proportion as in the central countries (every second person), but at the same time, a high degree of polarization can be demonstrated in the time spent gaming. Based on our results, players can be predicted with high reliability based on player preferences, that is, game types, motivations, and shopping habits. However, it is worth supplementing these categories with players' socio-demographic characteristics. Our research contributes to a deeper understanding of the factors and causal relationships that determine video gamers in semi-peripheral countries; moreover, it sheds light on the distinguishing variables that function as group builders.