TY - GEN
T1 - Enabling Physical Crowdsourcing On-the-Go with Context-Sensitive Notifications
AU - Kim, Yongsung
AU - Harburg, Emily
AU - Azria, Shana
AU - Gerber, Elizabeth
AU - Gergle, Darren
AU - Zhang, Haoqi
N1 - Publisher Copyright:
Copyright © 2015, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.
PY - 2015/11/12
Y1 - 2015/11/12
N2 - This paper introduces the idea of sending timely notifications to potential helpers to complete small tasks on-the-go with minimal effort to them and maximal benefit to the system. We present two on-the-go crowdsourcing systems: Libero for package delivery, and CrowdFound for finding lost items. To encourage contributions, we introduce notification techniques that present task opportunities when potential helpers are likely to accept. To direct people to regions where help is most needed, we introduce techniques for tracking a person’s location within a task region and directing their attention based on task history. Evaluation studies demonstrate the feasibility of on-the-go crowdsourcing and investigate questions over the likelihood of task completion, the perceived cost of disruption, and the effectiveness of tracking and coordination.
AB - This paper introduces the idea of sending timely notifications to potential helpers to complete small tasks on-the-go with minimal effort to them and maximal benefit to the system. We present two on-the-go crowdsourcing systems: Libero for package delivery, and CrowdFound for finding lost items. To encourage contributions, we introduce notification techniques that present task opportunities when potential helpers are likely to accept. To direct people to regions where help is most needed, we introduce techniques for tracking a person’s location within a task region and directing their attention based on task history. Evaluation studies demonstrate the feasibility of on-the-go crowdsourcing and investigate questions over the likelihood of task completion, the perceived cost of disruption, and the effectiveness of tracking and coordination.
UR - http://www.scopus.com/inward/record.url?scp=85049676725&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85049676725&partnerID=8YFLogxK
U2 - 10.1609/hcomp.v3i1.13252
DO - 10.1609/hcomp.v3i1.13252
M3 - Conference contribution
AN - SCOPUS:85049676725
SN - 978-1577357414
T3 - Proceedings of the 3rd AAAI Conference on Human Computation and Crowdsourcing, HCOMP 2015
SP - 14
EP - 15
BT - Proceedings of the 3rd AAAI Conference on Human Computation and Crowdsourcing, HCOMP 2015
A2 - Gerber, Elizabeth
A2 - Ipeirotis, Panos
PB - AAAI Press
T2 - 3rd AAAI Conference on Human Computation and Crowdsourcing, HCOMP 2015
Y2 - 8 November 2015 through 11 November 2015
ER -