Assessing Player Profiles of Achievement, Affiliation, and Power Motivation Using Electroencephalography

Abstract

Individual differences in motivation can explain why people act differently in the same situation, and which aspects of a game people with different motive profiles may find most engaging. However, identifying a player’s motive profile from data available during gameplay remains an open research question. Besides a range of subjective and objective techniques for identifying player motivation, electroencephalography (EEG) technology could offer an automatic, objective technique for identifying the profile that best describes a given player. This article proposes a framework to measure player profiles of achievement, affiliation, and power motivation using EEG signals during their engagement within a game. First, an abstract mini-game is proposed to evaluate a player’s motivation. In the mini-game, each human player interacts with four nonplayer characters to gain <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">fortune</i> or <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">friendship</i> through an individual play phase and a social network phase. The game is used within an experimental scenario to collect players’ actions and EEG signals. In addition, data from a psychological test are used to establish ground truth. We propose three subject labeling schemes using the output of the psychological test. Based on a player’s motive profile, behavioral indicators and EEG data analysis indicate that assessing a player’s motive profile is more robust from EEG signals than from behavioral data.