Studying the Effects of Task Notification Policies on Participation and Outcomes in On-the-Go Crowdsourcing

Yongsung Kim, Emily Harburg, Shana Azria, Aaron David Shaw, Elizabeth Gerber, Darren Gergle, Haoqi Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

Recent years have seen the growth of physical crowdsourcing systems (e.g., Uber; TaskRabbit) that motivate large numbers of people to provide new and improved physical tasking and delivery services on-demand. In these systems, opportunistically relying on people to make convenient contributions may lead to incomplete solutions, while directing people to do inconvenient tasks requires high incentives. To increase people's willingness to participate and reduce the need to incentivize participation, we study on-the-go crowdsourcing as an alternative approach that suggests tasks along people's existing routes that are conveniently on their way. We explore as a first step in this paper the design of task notification policies that decide when, where, and to whom to suggest tasks. Situating our work in the context of practical problems such as package delivery and lost-and-found searches, we conducted controlled experiments that show how small changes in task notification policy can influence individual participation and actions in significant ways that in turn affect system outcomes. We discuss the implications of our findings on the design of future on-the-go crowdsourcing technologies.

Original languageEnglish (US)
Title of host publicationProceedings of the 4th AAAI Conference on Human Computation and Crowdsourcing, HCOMP 2016
EditorsArpita Ghosh, Matthew Lease
PublisherAAAI Press
Pages99-108
Number of pages10
ISBN (Electronic)9781577357742
ISBN (Print)978-1577357742
StatePublished - Nov 3 2016
Event4th AAAI Conference on Human Computation and Crowdsourcing, HCOMP 2016 - Austin, United States
Duration: Oct 30 2016Nov 3 2016

Publication series

NameProceedings of the 4th AAAI Conference on Human Computation and Crowdsourcing, HCOMP 2016

Conference

Conference4th AAAI Conference on Human Computation and Crowdsourcing, HCOMP 2016
Country/TerritoryUnited States
CityAustin
Period10/30/1611/3/16

Funding

We thank members of the Design, Technology, and Research program and the Delta Lab for their valuable feedback and helpful discussions. This work was funded by National Science Foundation grant #1618096, a Microsoft Research FUSE Labs Award, and a Segal Design Cluster fellowship.

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Human-Computer Interaction

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