Antisocial behavior such as negative gossip, cheating, or bullying can be contagious, spreading from individual to individual and rippling through social networks. Previous experimental research has suggested that individuals who either experience or observe antisocial behavior become more likely to behave antisocially. Here, we distinguish between victimization and observation using an observational study. We apply temporal network analysis on large-scale digital trace data to study the spread of cheating in online gaming. We analyze 1,146,941 matches of the multiplayer online game PlayerUnknown's Battlegrounds, in which up to 100 players compete individually or in teams against strangers. We identify temporal motifs in which a player who is killed by or observes cheaters starts cheating, and evaluate the extent to which these motifs would appear if we preserve the team and interaction structure but assume an alternative sequence of events. The results suggest that social contagion is only likely to exist for those who both experience and observe cheating multiple times. The findings point to strategies for targeted interventions to stem the spread of cheating and antisocial behavior in online communities, schools, organizations, and sports.

中文翻译：

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大规模网络分析揭示欺骗通过受害和观察传播

负面八卦、欺骗或欺凌等反社会行为可能具有传染性，会在个人之间传播，并在社交网络中蔓延。先前的实验研究表明，经历或观察到反社会行为的人更有可能表现出反社会行为。在这里，我们使用观察性研究区分受害和观察。我们对大规模数字跟踪数据应用时间网络分析来研究在线游戏中作弊的传播。我们分析了多人在线游戏 PlayerUnknown's Battlegrounds 的 1,146,941 场比赛，其中多达 100 名玩家单独或组队对抗陌生人。我们确定了被作弊者杀死或观察到作弊者开始作弊的时间主题，并评估如果我们保留团队和交互结构但假设事件的替代顺序，这些主题会出现的程度。结果表明，只有那些多次经历和观察到作弊的人才可能存在社会传染。研究结果指出了有针对性的干预策略，以阻止作弊和反社会行为在在线社区、学校、组织和体育运动中的蔓延。