TY - GEN
T1 - Modeling sharing decision of campus safety reports and its design implications to mobile crowdsourcing for safety
AU - Huang, Yun
AU - White, Corey
AU - Xia, Huichuan
AU - Wang, Yang
N1 - Publisher Copyright:
© 2015 ACM.
PY - 2015/8/24
Y1 - 2015/8/24
N2 - 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.
AB - 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.
KW - Decision model
KW - Mobile crowdsourcing
KW - Public safety
UR - http://www.scopus.com/inward/record.url?scp=84959348637&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84959348637&partnerID=8YFLogxK
U2 - 10.1145/2785830.2785889
DO - 10.1145/2785830.2785889
M3 - Conference contribution
AN - SCOPUS:84959348637
T3 - MobileHCI 2015 - Proceedings of the 17th International Conference on Human-Computer Interaction with Mobile Devices and Services
SP - 400
EP - 409
BT - MobileHCI 2015 - Proceedings of the 17th International Conference on Human-Computer Interaction with Mobile Devices and Services
PB - Association for Computing Machinery, Inc
T2 - 17th International Conference on Human-Computer Interaction with Mobile Devices and Services, MobileHCI 2015
Y2 - 24 August 2015 through 27 August 2015
ER -