Crowdsourcing as a Tool for Research: Methodological, Fair, and Political Considerations
Crowdsourcing as a Tool for Research: Methodological, Fair, and Political Considerations
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DOI：
10.1177/02704676211003808
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发表时间：
2020-10
影响因子：
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通讯作者：
Stephen C. Rea;Hanzelle Kleeman;Qin Zhu;Benjamin Gilbert;Chuan Yue
中科院分区：
文献类型：
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作者：
Stephen C. Rea;Hanzelle Kleeman;Qin Zhu;Benjamin Gilbert;Chuan Yue
众包平台是学术研究人员的强大工具。支持者声称，众包可以帮助研究人员快速、经济地招募足够多具有不同背景的人类受试者，以产生显着的统计能力，而批评者则对不可靠的数据质量、劳动力剥削以及研究人员和工人之间不平等的权力动态表示担忧。我们从三个维度审视这些担忧：方法、公平性和政治。我们发现研究人员为众包任务提供了截然不同的补偿率，并通过使用特定于平台的工具和用户验证方法来解决对数据有效性的潜在担忧。此外，工人的很大一部分收入依赖于众包平台，他们的动机更多是出于对失去工作机会的恐惧，而不是特定的补偿率，并且因缺乏透明度和偶尔受到求职者的不公平对待而感到沮丧。最后，我们讨论了关键计算学者解决众包问题的建议、实施这些解决方案的挑战以及未来研究的潜在途径。
Crowdsourcing platforms are powerful tools for academic researchers. Proponents claim that crowdsourcing helps researchers quickly and affordably recruit enough human subjects with diverse backgrounds to generate significant statistical power, while critics raise concerns about unreliable data quality, labor exploitation, and unequal power dynamics between researchers and workers. We examine these concerns along three dimensions: methods, fairness, and politics. We find that researchers offer vastly different compensation rates for crowdsourced tasks, and address potential concerns about data validity by using platform-specific tools and user verification methods. Additionally, workers depend upon crowdsourcing platforms for a significant portion of their income, are motivated more by fear of losing access to work than by specific compensation rates, and are frustrated by a lack of transparency and occasional unfair treatment from job requesters. Finally, we discuss critical computing scholars’ proposals to address crowdsourcing’s problems, challenges with implementing these resolutions, and potential avenues for future research.