This study, using conventional content analysis, examined a corpus of #MeToo tweets from the first day the hashtag went viral, October 16th 2017. Of the 10,546 #MeToo tweets collected, three major categories were identified: these included #MeToo Facilitated Self-Disclosure, Messages of Support, and Calling Out Poor Behaviour with 5,243, 1,556, and 1207 tweets, respectively. The majority of disclosure tweets detailed experiences of sexual assault (44%) and experiences that occurred during childhood (29.4%). The results of this study offer valuable insights regarding the information users chose to share during the first day of the #MeToo movement and the nature of sexual harassment and assault experienced by these individuals. This information may be used by policymakers to identify and implement means to reduce the prevalence of sexual harassment and assault.

这项研究使用传统的内容分析，从 2017 年 10 月 16 日话题标签病毒式传播的第一天起检查了#MeToo 推文的语料库。在收集的 10,546 条#MeToo 推文中，确定了三个主要类别：其中包括#MeToo 促进自我披露，的信息支持和呼叫行为差分别有 5,243、1,556 和 1207 条推文。大多数披露在推特上发布了详细的性侵犯经历 (44%) 和童年时期的经历 (29.4%)。这项研究的结果为用户在#MeToo 运动的第一天选择分享的信息以及这些人所经历的性骚扰和攻击的性质提供了宝贵的见解。政策制定者可以使用这些信息来确定和实施减少性骚扰和攻击流行的方法。