家庭暴力
心理学
人为因素与人体工程学
毒物控制
自杀预防
多级模型
伤害预防
社会心理学
发展心理学
医疗急救
医学
计算机科学
机器学习
作者
Khandis R. Blake,Siobhan O’Dean,James Lian,Thomas F. Denson
标识
DOI:10.1177/0956797620968529
摘要
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.
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