Process Mining for Game Analytics
In the latest Process Mining Café, we invited prof. Magy Seif El-Nasr to talk about data analytics for games.
Magy gave an overview of the different types of games and traditional game analytics. Recently, her research group at the department of Computational Media at UC Santa Cruz has used process mining to understand the usage flows of educational games, the strategies people use to solve puzzle games, and sentiment flows in teamwork games. We talked about the ethics of using game analytics to make games more addictive and discussed the challenges of abstracting the data to the right level.
If you missed the live broadcast or want to re-watch the café, you can now watch the recording here. Thanks again to Magy and all of you for joining us!
Here are the links that we mentioned during the session:
Magy’s first book is a collection of edited papers focusing on the data collected and analyzed by video game vendors to improve the game player experience: Game Analytics.
Maximizing the Value of Player Data, Editors: Magy Seif El-Nasr, Anders Drachen, Alessandro Canossa. Springer, 2013.
Magy’s second book is a textbook on game analytics. Game Data Science by Magy Seif El-Nasr, Truong-Huy D. Nguyen, Alessandro Canossa, and Anders Drachen. Oxford University Press, 2021.
Video of the parallel game
Finding the right level of abstraction in soccer and robot soccer
Contact us via firstname.lastname@example.org if you have questions or suggestions for the café anytime.
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