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Job alerts in the wild: Study of expectations and effects of location-based notifications in an existing mobile crowdsourcing application

: Reinhardt, D.; Michalak, M.; Lokaiczyk, R.


Association for Computing Machinery -ACM-; Association for Computing Machinery -ACM-, Special Interest Group on Applied Computing -SIGAPP-; Association for Computing Machinery -ACM-, Special Interest Group on Embedded Systems -SIGBED-:
MobiQuitous 2016, 13th International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services. Proceedings : Hiroshima, Japan, November 28 - December 01, 2016
New York: ACM, 2016
ISBN: 978-1-4503-4750-1
ISBN: 978-1-4503-4781-5
International Conference on Mobile and Ubiquitous Systems - Computing, Networking and Services (MobiQuitous) <13, 2016, Hiroshima>
Conference Paper
Fraunhofer FKIE ()

Mobile crowdsourcing applications leverage volunteers to collect information using their personal devices. It is hence vital to foster the volunteers' engagement and their contributions to ensure the long-term viability of these applications. A method to reach this goal is to notify participants about new tasks in their physical proximity. Such location-based notifications can however impact the users' experiences, disclose their location, and/or incur additional resource consumption. In this paper, we therefore investigate the potential worthiness of introducing location-based notifications in the wild. Our analysis includes the perspectives of both potential users and campaign managers. To this end, we have conducted two questionnaire-based studies counting 335 participants in total. By doing so, we gain insights about the participants' expectations and the value attributed to invested resources. We further identify significant factors that influence their readiness to activate this new function. Finally, we measure the impact of job alerts and rewards on both the quantity and quality of users' contributions. Consequently, our findings can help campaign administrators in the design of future crowdsensing applications.