Silence breaking: sex crime reporting in the MeToo era
利用谷歌搜索指数和机器学习构建美国地方对女性态度的指标，发现MeToo运动在性别歧视程度较低的地区关注度更高，且这些地区性犯罪举报数量显著增加，表明举报行为变化而非实际案件增加。
Abstract This paper introduces an index for assessing local attitudes toward women in the United States, leveraging the Google search index and a machine learning methodology. Exploiting the constructed measure of sexism, our investigation reveals that the #MeToo movement garnered greater attention in areas characterized by low measured sexism in the pre-MeToo era. Additionally, a substantial increase in reported sex crimes is observed in those areas post-MeToo compared to those with higher sexism measures. Further empirical findings indicate that the surge in documented sex crimes primarily stems from changes in reporting behavior rather than substantive shifts in actual incidents.