A mathematical model of the finding of usability problems
INTERCHI '93 Proceedings of the INTERCHI '93 conference on Human factors in computing systems
The human-computer interaction handbook
Agents that care: investigating the effects of orientation of emotion exhibited by an embodied computer agent
Using frustration in the design of adaptive videogames
Proceedings of the 2004 ACM SIGCHI International Conference on Advances in computer entertainment technology
Measuring emotional valence during interactive experiences: boys at video game play
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Playing Video Games: Motives, Responses, and Consequences (Lea's Communication Series)
Playing Video Games: Motives, Responses, and Consequences (Lea's Communication Series)
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Defining personas in games using metrics
Future Play '08 Proceedings of the 2008 Conference on Future Play: Research, Play, Share
Improving academic-industry collaboration for game research and education
Proceedings of the 4th International Conference on Foundations of Digital Games
Player modeling using self-organization in tomb raider: underworld
CIG'09 Proceedings of the 5th international conference on Computational Intelligence and Games
Feedback-based gameplay metrics: measuring player experience via automatic visual analysis
Proceedings of The 8th Australasian Conference on Interactive Entertainment: Playing the System
How responsiveness affects players' perception in digital games
Proceedings of the ACM Symposium on Applied Perception
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Frustration, in small, calibrated doses, can be integral to an enjoyable game experience, but it is a very delicate balance: just a slightly excessive amount of frustration could compel players to terminate prematurely the experience. Another factor with high relevance when analyzing player frustration is the difference in personality between players: some are less willing to endure frustration and might give up on the game earlier than others. This article seeks to identify patterns of behavior that could point to potential frustration before players resolve to quit a game. The method should be applicable independently from the personalities of different players. Furthermore, in order for this method to be relevant during game production, it has been decided to avoid relying on large numbers of players, and instead depend on highly granular data and both qualitative approaches (direct observation of players) and quantitative research (data mining gameplay metrics). The result is a computational model of player frustration that, although applied to a single game (Kane & Lynch 2), is able to raise a red flag whenever a sequence of actions in the game could be interpreted as possible player frustration.