In-Video Game Player's Behavior Measurement using Big Five Personal Traits

The propagation of video games in the previous years has led to the emergence of new areas associated with the video game industry. One of these areas is exploring the emotions and the behaviors of players after playing a specific game within a controlled environment such as a computer lab. In this paper, we will introduce a new way of analyzing the emotions and the behavior of players outside a controlled environment and using in-game data rather than using traditional questionnaires and interviews. The proposed system is expected to be part of future Internet of Things (IoT) application that is needed for human interaction. We will analyze the player's personality using in-game data. The data is generated and collected using mobile developed video game. Then, the collected data is evaluated using a well-known personality traits model called big Five-Factor Model (FFM). In order to create a set of appropriate scenarios to analyze the player's personality based on FFM we developed a First Person Shooter (FPS) video game. Using this game, we managed to generate and collect in-game data from hundreds of people. The results show that it was able to study the player's behavior over FFM traits. It was shown that the FFM traits scores are improved by repeating the game.