Shape patterns in popularity series of video games
Leonardo R. Cunha, Arthur A. B. Pessa, Renio S. Mendes

TL;DR
This study analyzes the popularity patterns of nearly six thousand video games over eleven years, identifying five distinct shape clusters and examining their persistence over time.
Contribution
It introduces a data-driven clustering approach to categorize popularity series of video games based on their shape patterns.
Findings
Five main shape clusters identified: decreasing, hilly, increasing, valley, and bursty.
Approximately 50% of games show decreasing popularity patterns.
Most games tend to maintain their initial popularity pattern over time.
Abstract
In recent years, digital games have become increasingly present in people's lives both as a leisure activity or in gamified activities of everyday life. Despite this growing presence, large-scale, data-driven analyses of video games remain a small fraction of the related literature. In this sense, the present work constitutes an investigation of patterns in popularity series of video games based on monthly popularity series, spanning eleven years, for close to six thousand games listed on the online platform Steam. Utilizing these series, after a preprocessing stage, we perform a clustering task in order to group the series solely based on their shape. Our results indicate the existence of five clusters of shape patterns named decreasing, hilly, increasing, valley, and bursty, with approximately half of the games showing a decreasing popularity pattern, 20.7% being hilly, 11.8%…
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Taxonomy
TopicsArtificial Intelligence in Games · Digital Games and Media · Video Analysis and Summarization
