How online social behavior covaries with real-world outcomes remains poorly understood. We examined the relationship between the frequency of misogynistic attitudes expressed on Twitter and incidents of domestic and family violence that were reported to the Federal Bureau of Investigation. We tracked misogynistic tweets in more than 400 areas across 47 American states from 2013 to 2014. Correlation and regression analyses found that misogynistic tweets were related to domestic- and family-violence incidents in those areas. A cross-lagged model showed that misogynistic tweets positively predicted domestic and family violence 1 year later; however, this effect was small. Results were robust to several known predictors of domestic violence. Our findings identify geolocated online misogyny as co-occurring with domestic and family violence. Because the longitudinal relationship between misogynistic tweets and domestic and family violence was small and conducted at the societal level, more research with multilevel data might be useful in the prediction of future violence.

在线社交行为如何与现实世界的结果共变仍然知之甚少。我们研究了 Twitter 上表达的厌恶女性态度的频率与向联邦调查局报告的家庭暴力事件之间的关系。从 2013 年到 2014 年，我们在美国 47 个州的 400 多个地区跟踪了厌恶女性的推文。相关性和回归分析发现，厌恶女性的推文与这些地区的家庭暴力事件有关。交叉滞后模型表明，厌恶女性的推文在 1 年后积极预测家庭暴力；然而，这种影响很小。结果对家庭暴力的几个已知预测因素是稳健的。我们的研究结果表明，地理定位的在线厌女症与家庭暴力同时发生。