# MeTooMaastricht：构建聊天机器人帮助性骚扰幸存者
#MeTooMaastricht: Building a chatbot to assist survivors of sexual harassment
摘要：
受最近#MeToo社会运动的启发，我们正在构建一个聊天机器人，以帮助性骚扰案件的幸存者（专为马斯特里赫特市设计，但可以轻松扩展）。这项工作背后的动机有两个方面：适当地帮助这类事件的幸存者，将他们引导到能够为他们提供帮助的适当机构，并增加事件记录，以便收集更多关于目前未报告的骚扰案件的数据。我们将问题分解为三个数据科学/机器学习组件：骚扰类型识别（视为分类问题），时空信息抽取（视为命名实体识别问题）和与用户对话（视为基于槽填充的聊天机器人）。我们能够达到超过98%的成功率识别骚扰或没有案件和约80%的特定类型的骚扰识别。地点和日期的识别准确率超过90%，时间发生的准确率接近80%。最后，聊天机器人的初步验证显示了进一步开发和部署这种有益于整个社会的工具的巨大潜力。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
