The growing prevalence of hate material on the Internet has led to mounting concerns from scholars and policymakers alike. While recent scholarship has explored predictors of exposure, perception, and participation in online hate, few studies have empirically examined the social factors that lead individuals to produce cyberhate. Therefore, this work examines the production of online hate using online survey data (N = 520) of youth and young adults collected in December 2017. We draw on two commonly-cited criminological theories, the General Theory of Crime (GTC) and Social Structure-Social Learning Theory (SSSL), to understand social factors that contribute to producing cyberhate. In addition, we consider whether a broader relationship exists between the production of online hate and support for President Trump, whose rhetoric has gained traction among far-right and alt-right communities that traffic in hate. Logistic regression results show limited support for GTC, as low self-control is not a significant correlate of producing cyberhate after other relevant variables are considered. We find more robust support for SSSL, as the production of cyberhate is associated with an individual’s social location, online associations, and differential reinforcement. Moreover, we find evidence that individuals who approve of President Trump’s job performance are more likely to produce online hate.

互联网上仇恨材料的日益普及，引起了学者和决策者的越来越多的关注。尽管最近的一项研究探索了暴露，知觉和参与网络仇恨的预测因素，但很少有研究从经验上考察导致个人产生网络仇恨的社会因素。因此，这项工作使用在线调查数据来检验在线仇恨的产生（N = 520）的年轻人和年轻人在2017年12月收集的数据。我们借鉴两种常见的犯罪学理论，即犯罪通用理论（GTC）和社会结构社会学习理论（SSSL），以了解有助于生产的社会因素网络仇恨。此外，我们考虑在线仇恨的产生与对特朗普总统的支持之间是否存在更广泛的关系。特朗普总统的言论已在仇恨行为的极右派和另类右派社区中引起关注。Logistic回归结果显示对GTC的支持有限，因为在考虑了其他相关变量之后，低自我控制并不是产生网络仇恨的重要关联。我们发现，对SSSL的支持更加强大，因为网络仇恨的产生与个人的社交位置，在线关联和差异化强化相关。