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过于轶事化,难以置信?机械 Turk 并非全是机器人和不良数据:对 Webb 和 Tangney(2022)的回应。

Too Anecdotal to Be True? Mechanical Turk Is Not All Bots and Bad Data: Response to Webb and Tangney (2022).

机构信息

Department of Psychology, Bowling Green State University.

Department of Management and Entrepreneurship, School of Business, Virginia Commonwealth University.

出版信息

Perspect Psychol Sci. 2024 Nov;19(6):900-907. doi: 10.1177/17456916241234328. Epub 2024 Mar 7.

Abstract

In response to Webb and Tangney (2022) we call into question the conclusion that data collected on Amazon's Mechanical Turk (MTurk) was "at best-only 2.6% valid" (p. 1). We suggest that Webb and Tangney made certain choices during the study-design and data-collection process that adversely affected the quality of the data collected. As a result, the anecdotal experience of these authors provides weak evidence that MTurk provides low-quality data as implied. In our commentary we highlight best practice recommendations and make suggestions for more effectively collecting and screening online panel data.

摘要

针对 Webb 和 Tangney(2022)的观点,我们对“在亚马逊的 Mechanical Turk(MTurk)上收集的数据‘最多只有 2.6%是有效的’”这一结论提出质疑。我们认为,Webb 和 Tangney 在研究设计和数据收集过程中做出了某些选择,这些选择对收集数据的质量产生了不利影响。因此,这些作者的轶事经验提供了微弱的证据,表明 MTurk 提供的是低质量的数据。在我们的评论中,我们强调了最佳实践建议,并提出了更有效地收集和筛选在线面板数据的建议。

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