  Inspired by the recent social movement of #MeToo, we are building a chatbot
to assist survivors of sexual harassment cases (designed for the city of
Maastricht but can easily be extended). The motivation behind this work is
twofold: properly assist survivors of such events by directing them to
appropriate institutions that can offer them help and increase the incident
documentation so as to gather more data about harassment cases which are
currently under reported. We break down the problem into three data
science/machine learning components: harassment type identification (treated as
a classification problem), spatio-temporal information extraction (treated as
Named Entity Recognition problem) and dialogue with the users (treated as a
slot-filling based chatbot). We are able to achieve a success rate of more than
98% for the identification of a harassment-or-not case and around 80% for the
specific type harassment identification. Locations and dates are identified
with more than 90% accuracy and time occurrences prove more challenging with
almost 80%. Finally, initial validation of the chatbot shows great potential
for the further development and deployment of such a beneficial for the whole
society tool.
