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Understanding Workers, Developing Effective Tasks, and Enhancing Marketplace Dynamics: A Study of a Large Crowdsourcing Marketplace

Summary: Large-scale crowdsourcing dataset (27M microtasks, 70k+ workers) informs task design and marketplace dynamics, a unique scale for crowdsourcing research. Longitudinal analysis (2012–2016) reveals worker attention spans, lifetimes, and marketplace load, providing data-management guidance for platform design and optimization. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
11577
Venue
VLDB
Year
2017
Pagerank
4.4904732e-05
Overall Rank
8,510 | 40.86%
DOI
-

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Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
2,348 RPT: Relational Pre-trained Transformer Is Almost All You Need towards Democratizing Data Preparation 2021 VLDB 8.9903659e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 7 of 7 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
94 CrowdDB: Answering Queries with Crowdsourcing 2011 SIGMOD 0.00051273089
246 Crowdsourced Databases: Query Processing with People 2011 CIDR 0.00030952631
854 So Who Won? Dynamic Max Discovery with the Crowd 2012 SIGMOD 0.00015879917
1,491 CDAS: A Crowdsourcing Data Analytics System 2012 VLDB 0.00011685731
3,104 Crowd Mining 2013 SIGMOD 7.5577057e-05
4,483 Optimal Crowd-Powered Rating and Filtering Algorithms 2014 VLDB 6.1431599e-05
7,178 Towards Globally Optimal Crowdsourcing Quality Management: The Uniform Worker Setting 2016 SIGMOD 4.80398e-05
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