Data-Driven Study of Long-Term Gaming Experience

inproceedings
2022
International Conference on Quality of Multimedia Experience · QoMEX

Abstract

A subset of massively multiplayer online games (MMOG) feature long-term game rounds in which players interact for months or even years. The player experience of such long-term games cannot be entirely captured by current study methods, in particular not at scale assessing large player populations. To address this challenge, we posit that long-term, round based games such as Tribal Wars (browser-based) enable a data-driven perspective on long-term game dynamics and experience. In a preliminary study, we monitor and characterize the entire longitudinal game state of a Tribal Wars round that was played by 16k players for 1.5 years, enabling us to investigate behavioral patterns of all active players. We identify features that capture the in-game success and relate to the player experience. We show that only successful players keep up playing. We open source our dataset enabling reproducibility & future research.

Authors

Jens Helge Reelfs

Artifacts

Topics

Computational Social Science Gaming Quality of Experience (QoE) Long-Term Player Behavior Analysis Data-Driven Social Network Studies User Engagement Metrics in Online Games Behavioral Analytics in MMOGs