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 language | English (US) |
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Title of host publication | CHI 2015 - Extended Abstracts Publication of the 33rd Annual CHI Conference on Human Factors in Computing Systems |
Subtitle of host publication | Crossings |
Publisher | Association for Computing Machinery |
Pages | 1537-1542 |
Number of pages | 6 |
Volume | 18 |
ISBN (Electronic) | 9781450331463 |
DOIs | |
State | Published - Apr 18 2015 |
Event | 33rd Annual CHI Conference on Human Factors in Computing Systems, CHI EA 2015 - Seoul, Korea, Republic of Duration: Apr 18 2015 → Apr 23 2015 |
Other
Other | 33rd Annual CHI Conference on Human Factors in Computing Systems, CHI EA 2015 |
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Country/Territory | Korea, Republic of |
City | Seoul |
Period | 4/18/15 → 4/23/15 |
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