Open Player Modeling: Empowering Players through Data Transparency
Jichen Zhu, Magy Seif El-Nasr

TL;DR
This paper introduces Open Player Modeling, a new research area focused on making game player data and models transparent to enhance user understanding and engagement, supported by a synthesis of related fields and a case study.
Contribution
It defines the design space of Open Player Models and highlights open research problems, bridging game development with data transparency practices from related disciplines.
Findings
Identified key open problems in open player modeling
Presented a case study demonstrating potential benefits
Synthesized insights from Intelligent User Interface and Learning Science
Abstract
Data is becoming an important central point for making design decisions for most software. Game development is not an exception. As data-driven methods and systems start to populate these environments, a good question is: can we make models developed from this data transparent to users? In this paper, we synthesize existing work from the Intelligent User Interface and Learning Science research communities, where they started to investigate the potential of making such data and models available to users. We then present a new area exploring this question, which we call Open Player Modeling, as an emerging research area. We define the design space of Open Player Models and present exciting open problems that the games research community can explore. We conclude the paper with a case study and discuss the potential value of this approach.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsSports Analytics and Performance · Artificial Intelligence in Games · Data Visualization and Analytics
