Context & Inspiration Discussions on Wikipedia are a crucial mechanism for editors to coordinate their work of curating the world’s knowledge. Unfortunately discussions are not only the locus of coordination and cooperation; they are also a major avenue by which editors experience toxicity and harassment. There has been growing concern among the community, the WMF, and the WMF Board about the impact harassment has on community health and a commitment to seriously engage the problem. In collaboration with the Jigsaw/Conversation AI team, Wikimedia Research we are exploring automated detection of toxic comments using machine learning models. These models allow us to analyze the dynamics and impact of comment-level harassment in talk page discussions at scale. They may also be used to build tools to visualize and possibly intervene in the problem. Content A corpus of discussion comments from English Wikipedia talk pages. Comments are grouped into different files by year. Comments are generated by computing diffs over the full revision history and extracting the content added for each revision. See [our wikipedia page][1] for documentation of the schema and our research paper for documentation on the data collection and processing methodology. The questionnaire used to generate the dataset is available here: https://github.com/ewulczyn/wiki-detox/blob/master/src/modeling/attack_question.png [1]: https://meta.wikimedia.org/wiki/Research:Detox/Data_Release