Unpacking Large-Scale Usage of Community-Sourced Risk Systems

Assistant Professor Yun Huang will present the IS 400 Colloquium, "Unpacking Large-Scale Usage of Community-Sourced Risk Systems."

Abstract: An increasing number of safety departments in organizations across the U.S. are offering community-sourced risk systems that allow their local community members to report potential risks, such as hazards, suspicious events, ongoing incidents, and crimes, through mobile apps. These systems are designed for the safety departments to take action to prevent or reduce the severity of situations that may harm the community. However, little is known about the actual use of such community-sourced risk systems from the perspective of both community members and the safety departments. In this talk, I will present our recent work—a comprehensive system log analysis of a community-sourced risk system that has been used by more than two hundred universities and colleges. This study is the first large-scale empirical analysis of community-sourced risk systems. Our findings revealed a mismatch between what the safety departments expected to receive and what their community members actually reported. We also identified several factors (e.g., anonymity, organization, and tip type) that were associated with the safety departments' responses to their community members' tips. Our findings provide design implications for chatbot-enabled community-risk systems and make practical contributions for safety organizations and practitioners to improve community engagement. This work will be presented at ACM CSCW 2021 conference.

Questions? Contact Gaozheng Liu