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CrowdFound: A Mobile Crowdsourcing System to Find Lost Items On-the-Go

Authors:

Emily Harburg,

Yongsung Kim,

Elizabeth Gerber,

Haoqi ZhangAuthors Info & Claims

CHI EA '15: Proceedings of the 33rd Annual ACM Conference Extended Abstracts on Human Factors in Computing Systems

Pages 1537 - 1542

https://doi.org/10.1145/2702613.2732757

Published: 18 April 2015 Publication History

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Abstract

We present CrowdFound, a mobile crowdsourcing system to find lost items. CrowdFound allows users to input lost item descriptions on a map 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.

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Ray AChowdhury CBhattacharya SRoy S(2022)A survey of mobile crowdsensing and crowdsourcing strategies for smart mobile device usersCCF Transactions on Pervasive Computing and Interaction10.1007/s42486-022-00110-95:1(98-123)Online publication date: 15-Jul-2022
https://doi.org/10.1007/s42486-022-00110-9
Voulgaridis KAngelopoulos CChatzimisios P(2020)Circularity Principles in Crowdsourced Systems2020 Global Information Infrastructure and Networking Symposium (GIIS)10.1109/GIIS50753.2020.9248494(1-5)Online publication date: 28-Oct-2020
https://doi.org/10.1109/GIIS50753.2020.9248494
Phuttharak JLoke S(2019)A Review of Mobile Crowdsourcing Architectures and Challenges: Toward Crowd-Empowered Internet-of-ThingsIEEE Access10.1109/ACCESS.2018.28853537(304-324)Online publication date: 2019
https://doi.org/10.1109/ACCESS.2018.2885353
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Index Terms

CrowdFound: A Mobile Crowdsourcing System to Find Lost Items On-the-Go
1. Human-centered computing
  1. Collaborative and social computing
  2. Human computer interaction (HCI)

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Published In

CHI EA '15: Proceedings of the 33rd Annual ACM Conference Extended Abstracts on Human Factors in Computing Systems

April 2015

2546 pages

ISBN:9781450331463

DOI:10.1145/2702613

General Chairs:
Bo Begole
Huawei, USA
,
Jinwoo Kim
Yonsei University, Korea
,
Program Chairs:
Kori Inkpen
Microsoft Research, USA
,
Woontack Woo
KAIST, Korea

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

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Published: 18 April 2015

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CHI '15: CHI Conference on Human Factors in Computing Systems

April 18 - 23, 2015

Seoul, Republic of Korea

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CHI EA '15 Paper Acceptance Rate 379 of 1,520 submissions, 25%;

Overall Acceptance Rate 6,164 of 23,696 submissions, 26%

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Ray AChowdhury CBhattacharya SRoy S(2022)A survey of mobile crowdsensing and crowdsourcing strategies for smart mobile device usersCCF Transactions on Pervasive Computing and Interaction10.1007/s42486-022-00110-95:1(98-123)Online publication date: 15-Jul-2022
https://doi.org/10.1007/s42486-022-00110-9
Voulgaridis KAngelopoulos CChatzimisios P(2020)Circularity Principles in Crowdsourced Systems2020 Global Information Infrastructure and Networking Symposium (GIIS)10.1109/GIIS50753.2020.9248494(1-5)Online publication date: 28-Oct-2020
https://doi.org/10.1109/GIIS50753.2020.9248494
Phuttharak JLoke S(2019)A Review of Mobile Crowdsourcing Architectures and Challenges: Toward Crowd-Empowered Internet-of-ThingsIEEE Access10.1109/ACCESS.2018.28853537(304-324)Online publication date: 2019
https://doi.org/10.1109/ACCESS.2018.2885353
Wang YJia XJin QMa J(2016)Mobile crowdsourcing: framework, challenges, and solutionsConcurrency and Computation: Practice and Experience10.1002/cpe.378929:3Online publication date: 12-Feb-2016
https://doi.org/10.1002/cpe.3789

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Putting Users in Control of their Recommendations

Libero: On-the-go Crowdsourcing for Package Delivery

Recommendations for Crowdsourcing Services Based on Mobile Scenarios and User Trajectory Awareness

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