Using heuristics to evaluate the playability of games
CHI '04 Extended Abstracts on Human Factors in Computing Systems
GameFlow: a model for evaluating player enjoyment in games
Computers in Entertainment (CIE) - Theoretical and Practical Computer Applications in Entertainment
International Journal of Human-Computer Studies
Measurement-based characterization of a collection of on-line games
IMC '05 Proceedings of the 5th ACM SIGCOMM conference on Internet Measurement
A long-term study of a popular MMORPG
Proceedings of the 6th ACM SIGCOMM workshop on Network and system support for games
Flow and immersion in first-person shooters: measuring the player's gameplay experience
Future Play '08 Proceedings of the 2008 Conference on Future Play: Research, Play, Share
Identifying MMORPG bots: a traffic analysis approach
EURASIP Journal on Advances in Signal Processing - Special issue on signal processing applications in network intrusion detection systems
An analysis of WoW players' game hours
Proceedings of the 7th ACM SIGCOMM Workshop on Network and System Support for Games
Virtual item sales as a revenue model: identifying attributes that drive purchase decisions
Electronic Commerce Research
Proceedings of the 5th ACM SIGGRAPH Symposium on Video Games
World of warcraft avatar history dataset
MMSys '11 Proceedings of the second annual ACM conference on Multimedia systems
Characterizing virtual populations in massively multiplayer online role-playing games
MMM'10 Proceedings of the 16th international conference on Advances in Multimedia Modeling
Are all games equally cloud-gaming-friendly?: an electromyographic approach
Proceedings of the 11th Annual Workshop on Network and Systems Support for Games
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Online gaming has now become an extremely competitive business. As there are so many game titles released every month, gamers have become more difficult to please and fickle in their allegiances. Therefore, it would be beneficial if we could forecast how addictive a game is before publishing it on the market. With the capability of game addictiveness forecasting, developers will be able to continuously adjust the game design and publishers will be able to assess the potential market value of a game in its early development stages. In this paper, we propose to forecast a game's addictiveness based on players' emotional responses when they are first exploring the game. Based on the account activity traces of 11 commercial games, we develop a forecasting model that predicts a game's addictiveness index according to electromyographic measures of players' two facial muscles. We hope that with our methodology, the game industry could optimize the odds of successful investments and target more accurately the provision of a better entertaining experience.