Designing and Evaluating a Chatbot for Survivors of Image-Based Sexual Abuse

Designing and Evaluating a Chatbot for Survivors of Image-Based Sexual Abuse

연구 분야: Safety

학회: CHI '22: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems

Image-based sexual abuse (IBSA) is a severe social problem that causes survivors tremendous pain. IBSA survivors may encounter a lack of information and victim blame when seeking online and offline assistance. While institutions support survivors, they cannot be available 24 hours a day. Because the immediate reaction to IBSA is crucial to remove intimate images and prevent further distribution, survivors need first responders who are always accessible and do not blame them. Chatbots are constantly available, do not judge the conversation partner, and may deliver structured information and words of comfort. Therefore, we developed a chatbot to provide information and emotional support to IBSA survivors in dealing with their abuse. We analyzed nine chatbots for sexual violence survivors to identify common design elements. In addition, we sought advice from five professional counselors about the challenges survivors have while responding to their harm. We conducted a user study with 25 participants to determine the chatbot’s effectiveness in providing information and emotional support compared to internet search. The chatbot was better than the internet search regarding information organization, accessibility, and conciseness. Furthermore, the chatbot excels in providing emotional support to survivors. We discuss the survivor-centered information structure and design consideration of emotionally supportive conversation.