Games Mapper: Topological Data Analysis of Steam Genres
Provides a scalable, interpretable tool for game industry analysts to understand market structure and dynamics, though the method is an extension of existing Mapper algorithm.
Games Mapper uses topological data analysis to automatically segment video game genres into coherent subgenres and track their evolution over time, demonstrated on 10 years of Steam Simulation games.
The video game industry comprises a vast, continuously evolving landscape of themes and genres. For studios and publishers that navigate this competitive market, understanding the structural dynamics and temporal evolution of specific game categories is crucial for identifying viable entry points. In this paper, we introduce Games Mapper, a novel analytical tool based on the Mapper algorithm from topological data analysis. Unlike traditional clustering techniques, Games Mapper captures the continuous topological relationships between datasets over time (or other guiding variables). We extend the standard algorithm with an automated cluster labelling method, ensuring highly interpretable and interactive visualisations of genre evolution. To demonstrate the efficacy of our approach, we present a comprehensive case study on Simulation games released on Steam between 2015 and 2025. Games Mapper autonomously segments the genre into coherent, persistent subgenres, and captures dynamic market shifts. Ultimately, we provide a scalable, generalisable tool for researchers and industrials to unravel complex market structures and track the evolution of the Steam ecosystem.