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土耳其机器人超时工作:亚马逊土耳其机器人平台上参与者特征与行为如何随时间和日期变化

Turking Overtime: How Participant Characteristics and Behavior Vary Over Time and Day on Amazon Mechanical Turk.

作者信息

Arechar Antonio A, Kraft-Todd Gordon, Rand David G

机构信息

Department of Psychology, Yale University, 2 Hillhouse Ave. New Haven, CT 06511.

Department of Economics, Yale University, 2 Hillhouse Ave. New Haven, CT 06511.

出版信息

J Econ Sci Assoc. 2017 Jul;3(1):1-11. doi: 10.1007/s40881-017-0035-0. Epub 2017 May 16.

Abstract

Online experiments allow researchers to collect datasets at times not typical of laboratory studies. We recruit 2,336 participants from Amazon Mechanical Turk to examine if participant characteristics and behaviors differ depending on whether the experiment is conducted during the day versus night, and on weekdays versus weekends. Participants make incentivized decisions involving prosociality, punishment, and discounting, and complete a demographic and personality survey. We find no time or day differences in behavior, but do find that participants at nights and on weekends are less experienced with online studies; on weekends are less reflective; and at night are less conscientious and more neurotic. These results are largely robust to finer grained measures of time and day. We also find that those who participated earlier in the course of the study are more experienced, reflective, and agreeable, but less charitable than later participants.

摘要

在线实验使研究人员能够在非实验室研究的典型时间收集数据集。我们从亚马逊土耳其机器人平台招募了2336名参与者,以研究参与者的特征和行为是否因实验是在白天还是晚上、工作日还是周末进行而有所不同。参与者做出涉及亲社会行为、惩罚和折扣的激励决策,并完成一份人口统计学和性格调查。我们发现行为上没有时间或日期差异,但确实发现夜间和周末的参与者对在线研究的经验较少;周末的参与者思考较少;夜间的参与者责任心较差且更神经质。这些结果在更精细的时间和日期测量中基本稳健。我们还发现,在研究过程中较早参与的人比后来的参与者更有经验、更善于思考且更随和,但慈善程度较低。

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