Trying to understand a player's characteristics with regards to a computer game is a major line of research known as player modeling. The purpose of player modeling is typically the adaptation of the game itself.We present two studies that extend player modeling into player profiling by trying to identify abstract personality traits, such as the need for cognition and self-esteem, through a player's in-game behavior.We present evidence that game mechanics that can be broadly adopted by several game genres, such as hints and a player's self-evaluation at the end of a level, correlate with the aforementioned personality traits. We conclude by presenting future directions for research regarding this topic, discuss the direct applications for the games industry, and explore how games can be developed as profiling tools with applications to other contexts.
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Player behavioural modelling has grown from a means to improve the playing strength of computer programs that play classic games (e.g., chess), to a means for impacting the player experience and satisfaction in video games, as well as in cross-domain applications such as interactive storytelling. In this context, player behavioural modelling is concerned with two goals, namely (1) providing an interesting or effective game AI on the basis of player models and (2) creating a basis for game developers to personalise gameplay as a whole, and creating new user-driven game mechanics. In this article, we provide an overview of player behavioural modelling for video games by detailing four distinct approaches, namely (1) modelling player actions, (2) modelling player tactics, (3) modelling player strategies, and (4) player profiling. We conclude the article with an analysis on the applicability of the approaches for the domain of video games.
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New online stores and digital distribution methods have led to the development of alternative monetization models for video-games, such as free-to-play games with advertisements. Although there are many games using such models, until now the effect on the player experience from such interruptions has not been studied. In this controlled experiment, we requested that participants (N=236) play one of three different versions of a platformer game with: 1) no interruptions, 2) 30-second video advertisements, and 3) a multiple-choice questionnaire. We then evaluated the effects on the player experience. The study shows differences in their experiences, namely in: competence, immersion, annoyance, affects, and the reliability of the questionnaire answers. The contribution of this work is to identify which player experience variables are affected by interruptions, which can be valuable for selecting the business model and guiding the game design process.
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