Hit-or-wait: Coordinating opportunistic low-effort contributions to achieve global outcomes in on-the-go crowdsourcing

Yongsung Kim, Darren Gergle, Haoqi Zhang

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

14 Scopus citations

Abstract

We consider the challenge of motivating and coordinating large numbers of people to contribute to solving local, communal problems through their existing routines. In order to design such "on-the-go crowdsourcing" systems, there is a need for mechanisms that can effectively coordinate contributions to address problem solving needs in the physical world while leveraging people's existing mobility with minimal disruption. We thus introduce Hit-or-Wait, a general decision-theoretic mechanism that intelligently controls decisions over when to notify a person of a task, in ways that reason both about system needs across tasks and about a helper's changing patterns of mobility. Through simulations and a field study in the context of community-based lost-and-found, we demonstrate that using Hit-or-Wait enables a system to make efficient use of people's contributions with minimal disruptions to their routines without the need for explicit coordination. Interviews with field study participants further suggest that highlighting an individual's contribution to the global goal may help people value their contributions more.

Original languageEnglish (US)
Title of host publicationCHI 2018 - Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems
Subtitle of host publicationEngage with CHI
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450356206, 9781450356213
DOIs
StatePublished - Apr 20 2018
Event2018 CHI Conference on Human Factors in Computing Systems, CHI 2018 - Montreal, Canada
Duration: Apr 21 2018Apr 26 2018

Publication series

NameConference on Human Factors in Computing Systems - Proceedings
Volume2018-April

Other

Other2018 CHI Conference on Human Factors in Computing Systems, CHI 2018
Country/TerritoryCanada
CityMontreal
Period4/21/184/26/18

Funding

We thank members of the Design, Technology, and Research program and the Delta Lab for their valuable feedback and helpful discussions. We thank Kotaro Hara for helping with collecting road segment data from OpenStreetMap dataset. This work was funded by the National Science Foundation under Grant No. 1618096.

Keywords

  • Decision theory
  • Mobile crowdsourcing
  • Physical crowdsourcing

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Graphics and Computer-Aided Design

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