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Collaborative Majority Vote: Improving Result Quality in Crowdsourcing Marketplaces

In: Crowdsourcing

Author

Listed:
  • Dennis Nordheimer

    (University of Mannheim, Schloss)

  • Khrystyna Nordheimer

    (University of Mannheim, Schloss)

  • Martin Schader

    (University of Mannheim, Schloss)

  • Axel Korthaus

    (Victoria University International)

Abstract

Crowdsourcing markets, such as Amazon’s Mechanical Turk, are designed for easy distribution of micro-tasks to an on-demand scalable workforce. Improving the quality of the submitted results is still one of the main challenges for quality control management in these markets. Although beneficial effects of synchronous collaborationSynchronous collaboration on the quality of work are well-established in other domains, interaction and collaboration mechanismsCollaboration mechanism are not yet supported by most crowdsourcing platforms, and thus, not considered as a means of ensuring high-quality processing of tasks. In this paper, we address this challenge and present a new method that extends majority vote, one of the most widely used quality assurance mechanisms, enabling workers to interact and communicate during task execution. We illustrate how to apply this method to the basic scenarios of task execution and present the enabling technology for the proposed real-time collaborative extension. We summarize its positive impacts on the quality of results and discuss its limitations.

Suggested Citation

  • Dennis Nordheimer & Khrystyna Nordheimer & Martin Schader & Axel Korthaus, 2015. "Collaborative Majority Vote: Improving Result Quality in Crowdsourcing Marketplaces," Progress in IS, in: Wei Li & Michael N. Huhns & Wei-Tek Tsai & Wenjun Wu (ed.), Crowdsourcing, edition 127, pages 131-142, Springer.
    • Handle: RePEc:spr:prochp:978-3-662-47011-4_8
    DOI: 10.1007/978-3-662-47011-4_8
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