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Modeling Sharing Decision of Campus Safety Reports and Its Design Implications to Mobile Crowdsourcing for Safety

Current campus communication regarding safety-related issues can be improved for both efficiency and accessibility. We observed a unique opportunity to develop a mobile crowdsourcing system, which allows university community members to report safety related incidents to the campus police department and to share their reports with other users of the system. To better inform the design of such a system, we applied drift-diffusion models in cognitive psychology to model the effect of various factors on users' sharing tendency. We conducted a laboratory experiment with 30 participants. We also ran an MTurk study with 230 participants to explore the feature of anonymous sharing in the application design. In this paper we report various results, including the findings that the time of day, location, and type of crime each affects the likelihood and timeliness of sharing safety reports in several different ways. We also discuss the implications for design of mobile crowdsourcing systems for public safety in general.