Automatic Classification of Sexual Harassment Cases

In our case, the data was provided by Safecity India, which is a platform launched on 2012, that crowdsources personal stories of sexual harassment and abuse in public spaces [2]. They have collected over 10,000 stories from over 50 cities in India, Kenya, Cameroon, and Nepal. More specifically they provided us a .cvs Additionally to the focal tasks of this project and as part of the NLP channel we decided to automate the category classification based on the sexual harassment case descriptions. Performing this classification task manually is time-consuming and leaving it entirely on the hands of the victim could produce ambiguity in the discrimination of the categories.