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Privacy in Crowdsourcing: a Review of the Threats and Challenges

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Abstract

Crowdsourcing platforms such as Amazon Mechanical Turk (MTurk) are popular and widely used in both academic and non-academic realms, but privacy threats and challenges in crowdsourcing have not been extensively reviewed. To help push the field forward in important new directions, this paper first reviews the privacy threats in different types of crowdsourcing based on Solove’s taxonomy of privacy and Brabham’s typology of crowdsourcing. Then, the paper explores the privacy challenges associated with the characteristics of crowdsourcing task, platform, requesters, and crowd workers. These privacy challenges are discussed and categorized into both theoretical and practical challenges. Based on the review and discussion, this paper proposes a set of strategies to better understand and address many of the privacy threats and challenges in crowdsourcing. Finally, the paper concludes by suggesting research implications for the future work.

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  1. School of Information Studies, Syracuse University, 221 Hinds Hall, Syracuse, NY, 13210-1190, USA

    Huichuan Xia

  2. School of Information Studies, Syracuse University, 220 Hinds Hall, Syracuse, NY, 13244-1190, USA

    Brian McKernan

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Xia, H., McKernan, B. Privacy in Crowdsourcing: a Review of the Threats and Challenges. Comput Supported Coop Work 29, 263–301 (2020). https://doi.org/10.1007/s10606-020-09374-0

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