CrowdFound: A mobile crowdsourcing system to find lost items on-the-go

Emily Harburg, Yongsung Kim, Elizabeth M Gerber, Haoqi Zhang

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

6 Scopus citations

Abstract

We present CrowdFound, a mobile crowdsourcing system to find lost items. CrowdFound allows users to input lost item descriptions on a map [Figure 1] and then sends notifications to users passing near tagged areas. To assess the system's efficacy, we conducted interviews and user testing on CrowdFound. Our results show that users were able to find lost items when using a combination of the notification, map, and item description features. In addition, users were willing to deviate off path to look for lost items, particularly when exercising. Our findings also suggest socio-technical features to promote more effective on-the-go crowdsourced help on microtasks. This research builds our understanding of physical crowdsourcing as a tool for solving societal problems and suggests broader implications for utilizing mobile crowds. Copyright is held by the author/owner(s).

Original languageEnglish (US)
Title of host publicationCHI 2015 - Extended Abstracts Publication of the 33rd Annual CHI Conference on Human Factors in Computing Systems
Subtitle of host publicationCrossings
PublisherAssociation for Computing Machinery
Pages1537-1542
Number of pages6
Volume18
ISBN (Electronic)9781450331463
DOIs
StatePublished - Apr 18 2015
Event33rd Annual CHI Conference on Human Factors in Computing Systems, CHI EA 2015 - Seoul, Korea, Republic of
Duration: Apr 18 2015Apr 23 2015

Other

Other33rd Annual CHI Conference on Human Factors in Computing Systems, CHI EA 2015
Country/TerritoryKorea, Republic of
CitySeoul
Period4/18/154/23/15

Keywords

  • Help-seeking
  • Mobile crowdsourcing
  • On-the-go crowdsourcing
  • Physical crowdsourcing
  • Social computing

ASJC Scopus subject areas

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

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