Background: Sexual assault and sexual harassment are highly prevalent events that have become a focal point of public discourse since the #MeToo movement began in October of 2017. While there is a rich literature on these topics, previous studies have relied on focus groups or survey data to characterize women's expereinces. The social media conversation around the #MeToo movement provides the first opportunity to capture unprompted discourse on these topics. Objective: We aim to characterize the early conversation of the #MeToo movement using text analysis from Twitter data. Furthermore, we seek to create a timeline of the tweets and summerize the content of the conversation and revelations in the beginning of the movement. Methods: We begin by categorizing Twitter posts since October 14th, 2017. We focus on first person revelation of sexual assault and/or harassment with the #MeToo hashtag. We conduct content analysis to categorize the revealed events by severity, age at incident and the poster’s race/ethnicity. We then use quantitative text analyses to summarize characteristics of the revealed incidents. Results: We find in early conversations that many women revealed childhood experience of sexual assault and harassment. We find this across all races of the poster. Conclusion: Though the online #MeToo movement is not representative, social media users are younger, more liberal and better educated than non-users, the deluge of revelations highlight the severity and ubiquity of sexual assault experienced by all classes of women.