Cheaters in a gaming social network


The popularity of online gaming has raised significant interest in understanding the technological needs for supporting gaming platforms. Consequently, various studies characterized network traffic due to gaming, resource provisioning, work load prediction, and player churn in online games [1]. Other studies have focused on the psychological and social properties of gamers and gaming communities [5]. Gamers form strong communities around their activity, with recent work suggesting that explicitly defined relationships of gamers tend to be supported by real world relationships [6]. One major problem with gaming is cheating. For some cheaters, the motivation is monetary. Virtual goods are worth real world money on eBay, and online game economies provide a lucrative opportunity for cyber criminals [2]. For other cheaters, a competitive advantage and the desire to win is motivation enough [3]. In this work, we analyze how cheaters are embedded in the Steam Community, a large online social network for gaming with millions of active users. Cheaters are identified by an automated mechanism operated by the Steam gaming service and their profiles are permanently flagged in a publicly visible way. We analyze differences in gaming-specific properties of cheaters and non-cheaters. We also examine whether cheaters occupy a particular position in the social network when compared to non-cheaters, and characterize the relationships they have among themselves, and with noncheaters. Our study shows that cheaters are well embedded in the social network, having similar connectivity to non-cheaters; their social position is largely undistinguishable from that of fair players; and their geographic distribution does not correspond to real world population nor is it determined by the popularity of the Steam Community at a given real world location.

DOI: 10.1145/2160803.2160871

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@article{Blackburn2011CheatersIA, title={Cheaters in a gaming social network}, author={Jeremy Blackburn and Ramanuja Simha and Clayton Long and Xiang Zuo and Nicolas Kourtellis and John Skvoretz and Adriana Iamnitchi}, journal={SIGMETRICS Performance Evaluation Review}, year={2011}, volume={39}, pages={101-103} }