Process Mining for Game Analytics

• Published in: IEEE Conference on Computational Intelligence and Games (Print) pp. 1 - 4
• Main Authors: Elbert, Nico, Flath, Christoph M.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 05.08.2024
• Subjects: Conformance Checking; Game Analytics; Games; Heuristic algorithms; Industries; Player Behavior Analysis; Process mining; Software; Software algorithms; User Behavior Mining
• ISSN: 2325-4289
• DOI: 10.1109/CoG60054.2024.10645544

This paper explores the integration of process mining techniques and the User Behavior Mining (UBM) Framework within game analytics, using a expansive dataset from Age of Empires II. We demonstrate how these methodologies can be used to systematically analyze and interpret complex player behaviors across various skill levels. Employing techniques such as trace clustering and directly-follows-graphs, we identify distinct behavioral patterns and quantify differences in strategy adherence. Additionally, conformance checking reveals the impact of deviations from standard build orders on game outcomes. Our findings underscore the potential of PM and UBM as powerful diagnostic tools in game analytics, offering scalable and structured approaches to enhance player interaction understanding. The successful application of these methodologies not only introduces a scalable and structured approach to quantifying complex player dynamics but also opens up the entire range of process mining methodologies, algorithms, and software solutions available. This advancement enables the gaming industry to leverage sophisticated analytical tools previously confined to other domains.