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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
11576
Venue
VLDB
Year
2017
Pagerank
4.4943871e-05
Overall Rank
8,517 | 40.75%
DOI
-

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Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
2,349 RPT: Relational Pre-trained Transformer Is Almost All You Need towards Democratizing Data Preparation 2021 VLDB 8.9876423e-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 0.00051013264
249 Crowdsourced Databases: Query Processing with People 2011 CIDR 0.00030740523
859 So Who Won? Dynamic Max Discovery with the Crowd 2012 SIGMOD 0.00015870894
1,491 CDAS: A Crowdsourcing Data Analytics System 2012 VLDB 0.00011694982
3,100 Crowd Mining 2013 SIGMOD 7.5634778e-05
4,479 Optimal Crowd-Powered Rating and Filtering Algorithms 2014 VLDB 6.149053e-05
7,178 Towards Globally Optimal Crowdsourcing Quality Management: The Uniform Worker Setting 2016 SIGMOD 4.8085946e-05
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