全球智库信息集成服务系统(G2TT): Intertemporal Differences Among MTurk Workers: Time-Based Sample Variations and Implications for Online Data Collection

G2TT

来源类型	Publication
	Intertemporal Differences Among MTurk Workers: Time-Based Sample Variations and Implications for Online Data Collection
	Logan S. Casey; Jesse Chandler; and Adam Seth Levine
发表日期	2017-06-14
出版者	Sage Open
出版年	2017
语种	英语
概述	The online labor market Amazon Mechanical Turk (MTurk) is an increasingly popular source of respondents for social science research.",
摘要	The online labor market Amazon Mechanical Turk (MTurk) is an increasingly popular source of respondents for social science research. A growing body of research has examined the demographic composition of MTurk workers as compared with that of other populations. While these comparisons have revealed the ways in which MTurk workers are and are not representative of the general population, variations among samples drawn from MTurk have received less attention. This article focuses on whether MTurk sample composition varies as a function of time. Specifically, we examine whether demographic characteristics vary by (a) time of day, (b) day of week, and serial position (i.e., earlier or later in data collection), both (c) across the entire data collection and (d) within specific batches. We find that day of week differences are minimal, but that time of day and serial position are associated with small but important variations in demographic composition. This demonstrates that MTurk samples cannot be presumed identical across different studies, potentially affecting reliability, validity, and efforts to reproduce findings.
URL	https://www.mathematica.org/our-publications-and-findings/publications/intertemporal-differences-among-mturk-workers-time-based-sample-variations-and-implications
来源智库	Mathematica Policy Research (United States)
资源类型	智库出版物
条目标识符	http://119.78.100.153/handle/2XGU8XDN/488905
推荐引用方式 GB/T 7714	Logan S. Casey,Jesse Chandler,and Adam Seth Levine. Intertemporal Differences Among MTurk Workers: Time-Based Sample Variations and Implications for Online Data Collection. 2017.