A symbolic representation of time series, with implications for streaming algorithms
DMKD '03 Proceedings of the 8th ACM SIGMOD workshop on Research issues in data mining and knowledge discovery
Characterizing the influence of domain expertise on web search behavior
Proceedings of the Second ACM International Conference on Web Search and Data Mining
Sociable killers: understanding social relationships in an online first-person shooter game
Proceedings of the ACM 2011 conference on Computer supported cooperative work
Starcraft from the stands: understanding the game spectator
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Personifying programming tool feedback improves novice programmers' learning
Proceedings of the seventh international workshop on Computing education research
Using sequential observations to model and predict player behavior
Proceedings of the 6th International Conference on Foundations of Digital Games
A spatiotemporal visualization approach for the analysis of gameplay data
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Empirical analysis of user data in game software development
Proceedings of the ACM-IEEE international symposium on Empirical software engineering and measurement
Friends FTW! friendship and competition in halo: reach
Proceedings of the 2013 conference on Computer supported cooperative work
Identifying emergent behaviours from longitudinal web use
Proceedings of the adjunct publication of the 26th annual ACM symposium on User interface software and technology
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How do video game skills develop, and what sets the top players apart? We study this question of skill through a rating generated from repeated multiplayer matches called TrueSkill. Using these ratings from 7 months of games from over 3 million players, we look at how play intensity, breaks in play, skill change over time, and other games affect skill. These analyzed factors are then combined to model future skill and games played; the results show that skill change in early matches is a useful metric for modeling future skill, while play intensity explains eventual games played. The best players in the 7-month period, who we call "Master Blasters", have varied skill patterns that often run counter to the trends we see for typical players. The data analysis is supplemented with a 70 person survey to explore how players' self-perceptions compare to the gameplay data; most survey responses align well with the data and provide insight into player beliefs and motivation. Finally, we wrap up with a discussion about hiding skill information from players, and implications for game designers.