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arXiv 1702.01119cs.SIcs.CYcs.HCstat.AP
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任何人都可以成为巨魔:在线讨论中巨魔行为的原因

Anyone Can Become a Troll: Causes of Trolling Behavior in Online Discussions

Justin Cheng, Michael Bernstein, Cristian Danescu-Niculescu-Mizil, Jure Leskovec

摘要:

在网络社区中,反社会行为(如拖钓)会破坏建设性的讨论。虽然先前的工作表明,拖钓行为仅限于一个声音和反社会的少数,我们证明,普通人也可以从事这种行为。我们提出了两个主要的触发机制:个人的情绪,和讨论的周围环境(例如,暴露于先前的拖钓行为)。通过一个模拟在线讨论的实验,我们发现负面情绪和看到别人的巨魔帖子都显着增加了用户拖钓的概率,并将此概率增加了一倍。为了支持和扩展这些结果,我们通过对大型在线新闻讨论社区的数据驱动的纵向分析,研究了这些相同的机制如何在野外发挥作用。这项分析揭示了时间情绪的影响,并探讨了长期的重复接触拖钓模式。拖钓行为的预测模型表明,情绪和讨论背景一起可以更好地解释拖钓行为,而不是个人的拖钓历史。这些结果表明,在适当的情况下,普通人可以表现得像巨魔。

英文摘要:

In online communities, antisocial behavior such as trolling disrupts constructive discussion. While prior work suggests that trolling behavior is confined to a vocal and antisocial minority, we demonstrate that ordinary people can engage in such behavior as well. We propose two primary trigger mechanisms: the individual's mood, and the surrounding context of a discussion (e.g., exposure to prior trolling behavior). Through an experiment simulating an online discussion, we find that both negative mood and seeing troll posts by others significantly increases the probability of a user trolling, and together double this probability. To support and extend these results, we study how these same mechanisms play out in the wild via a data-driven, longitudinal analysis of a large online news discussion community. This analysis reveals temporal mood effects, and explores long range patterns of repeated exposure to trolling. A predictive model of trolling behavior shows that mood and discussion context together can explain trolling behavior better than an individual's history of trolling. These results combine to suggest that ordinary people can, under the right circumstances, behave like trolls.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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