Details
| Original language | English |
|---|---|
| Title of host publication | WWW 2015 Companion - Proceedings of the 24th International Conference on World Wide Web |
| Pages | 493-497 |
| Number of pages | 5 |
| ISBN (electronic) | 9781450334730 |
| Publication status | Published - 18 May 2015 |
| Event | 24th International Conference on World Wide Web, WWW 2015 - Florence, Italy Duration: 18 May 2015 → 22 May 2015 |
Abstract
Within the scope of this PhD proposal, we set out to inves- tigate two pivotal aspects that influence the effectiveness of crowdsourcing: (i) microtask design, and (ii) workers behav- ior. Leveraging the dynamics of tasks that are crowdsourced on the one hand, and accounting for the behavior of work- ers on the other hand, can help in designing tasks effciently. To help understand the intricacies of microtasks, we identify the need for a taxonomy of typically crowdsourced tasks. Based on an extensive study of 1000 workers on Crowd- Flower, we propose a two-level categorization scheme for tasks. We present insights into the task a nity of workers, e ort exerted by workers to complete tasks of various types, and their satisfaction with the monetary incentives. We also analyze the prevalent behavior of trustworthy and untrust- worthy workers. Next, we propose behavioral metrics that can be used to measure and counter malicious activity in crowdsourced tasks. Finally, we present guidelines for the effective design of crowdsourced surveys and set important precedents for future work.
Keywords
- Behavioral Patterns, Crowdsourcing, Microtasks, Workers
ASJC Scopus subject areas
- Computer Science(all)
- Computer Networks and Communications
- Computer Science(all)
- Software
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WWW 2015 Companion - Proceedings of the 24th International Conference on World Wide Web. 2015. p. 493-497.
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Make Hay while the Crowd Shines
T2 - 24th International Conference on World Wide Web, WWW 2015
AU - Gadiraju, Ujwal
AU - Nejdl, Wolfgang
AU - Dietze, Stefan
PY - 2015/5/18
Y1 - 2015/5/18
N2 - Within the scope of this PhD proposal, we set out to inves- tigate two pivotal aspects that influence the effectiveness of crowdsourcing: (i) microtask design, and (ii) workers behav- ior. Leveraging the dynamics of tasks that are crowdsourced on the one hand, and accounting for the behavior of work- ers on the other hand, can help in designing tasks effciently. To help understand the intricacies of microtasks, we identify the need for a taxonomy of typically crowdsourced tasks. Based on an extensive study of 1000 workers on Crowd- Flower, we propose a two-level categorization scheme for tasks. We present insights into the task a nity of workers, e ort exerted by workers to complete tasks of various types, and their satisfaction with the monetary incentives. We also analyze the prevalent behavior of trustworthy and untrust- worthy workers. Next, we propose behavioral metrics that can be used to measure and counter malicious activity in crowdsourced tasks. Finally, we present guidelines for the effective design of crowdsourced surveys and set important precedents for future work.
AB - Within the scope of this PhD proposal, we set out to inves- tigate two pivotal aspects that influence the effectiveness of crowdsourcing: (i) microtask design, and (ii) workers behav- ior. Leveraging the dynamics of tasks that are crowdsourced on the one hand, and accounting for the behavior of work- ers on the other hand, can help in designing tasks effciently. To help understand the intricacies of microtasks, we identify the need for a taxonomy of typically crowdsourced tasks. Based on an extensive study of 1000 workers on Crowd- Flower, we propose a two-level categorization scheme for tasks. We present insights into the task a nity of workers, e ort exerted by workers to complete tasks of various types, and their satisfaction with the monetary incentives. We also analyze the prevalent behavior of trustworthy and untrust- worthy workers. Next, we propose behavioral metrics that can be used to measure and counter malicious activity in crowdsourced tasks. Finally, we present guidelines for the effective design of crowdsourced surveys and set important precedents for future work.
KW - Behavioral Patterns
KW - Crowdsourcing
KW - Microtasks
KW - Workers
UR - http://www.scopus.com/inward/record.url?scp=84968552345&partnerID=8YFLogxK
U2 - 10.1145/2740908.2741748
DO - 10.1145/2740908.2741748
M3 - Conference contribution
AN - SCOPUS:84968552345
SP - 493
EP - 497
BT - WWW 2015 Companion - Proceedings of the 24th International Conference on World Wide Web
Y2 - 18 May 2015 through 22 May 2015
ER -