{"title":"好得不真实:来自 Mechanical Turk 的机器人和不良数据》(Too Good to Be True: Bots and Bad Data from Mechanical Turk.","authors":"Margaret A Webb, June P Tangney","doi":"10.1177/17456916221120027","DOIUrl":null,"url":null,"abstract":"<p><p>Psychology is moving increasingly toward digital sources of data, with Amazon's Mechanical Turk (MTurk) at the forefront of that charge. In 2015, up to an estimated 45% of articles published in the top behavioral and social science journals included at least one study conducted on MTurk. In this article, I summarize my own experience with MTurk and how I deduced that my sample was-at best-only 2.6% valid, by my estimate. I share these results as a warning and call for caution. Recently, I conducted an online study via Amazon's MTurk, eager and excited to collect my own data for the first time as a doctoral student. What resulted has prompted me to write this as a warning: it is indeed too good to be true. This is a summary of how I determined that, at best, I had gathered valid data from 14 human beings-2.6% of my participant sample (<i>N</i> = 529).</p>","PeriodicalId":19757,"journal":{"name":"Perspectives on Psychological Science","volume":null,"pages":null},"PeriodicalIF":10.5000,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Too Good to Be True: Bots and Bad Data From Mechanical Turk.\",\"authors\":\"Margaret A Webb, June P Tangney\",\"doi\":\"10.1177/17456916221120027\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Psychology is moving increasingly toward digital sources of data, with Amazon's Mechanical Turk (MTurk) at the forefront of that charge. In 2015, up to an estimated 45% of articles published in the top behavioral and social science journals included at least one study conducted on MTurk. In this article, I summarize my own experience with MTurk and how I deduced that my sample was-at best-only 2.6% valid, by my estimate. I share these results as a warning and call for caution. Recently, I conducted an online study via Amazon's MTurk, eager and excited to collect my own data for the first time as a doctoral student. What resulted has prompted me to write this as a warning: it is indeed too good to be true. This is a summary of how I determined that, at best, I had gathered valid data from 14 human beings-2.6% of my participant sample (<i>N</i> = 529).</p>\",\"PeriodicalId\":19757,\"journal\":{\"name\":\"Perspectives on Psychological Science\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":10.5000,\"publicationDate\":\"2024-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Perspectives on Psychological Science\",\"FirstCategoryId\":\"102\",\"ListUrlMain\":\"https://doi.org/10.1177/17456916221120027\",\"RegionNum\":1,\"RegionCategory\":\"心理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2022/11/7 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"PSYCHOLOGY, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Perspectives on Psychological Science","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.1177/17456916221120027","RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2022/11/7 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"PSYCHOLOGY, MULTIDISCIPLINARY","Score":null,"Total":0}
Too Good to Be True: Bots and Bad Data From Mechanical Turk.
Psychology is moving increasingly toward digital sources of data, with Amazon's Mechanical Turk (MTurk) at the forefront of that charge. In 2015, up to an estimated 45% of articles published in the top behavioral and social science journals included at least one study conducted on MTurk. In this article, I summarize my own experience with MTurk and how I deduced that my sample was-at best-only 2.6% valid, by my estimate. I share these results as a warning and call for caution. Recently, I conducted an online study via Amazon's MTurk, eager and excited to collect my own data for the first time as a doctoral student. What resulted has prompted me to write this as a warning: it is indeed too good to be true. This is a summary of how I determined that, at best, I had gathered valid data from 14 human beings-2.6% of my participant sample (N = 529).
期刊介绍:
Perspectives on Psychological Science is a journal that publishes a diverse range of articles and reports in the field of psychology. The journal includes broad integrative reviews, overviews of research programs, meta-analyses, theoretical statements, book reviews, and articles on various topics such as the philosophy of science and opinion pieces about major issues in the field. It also features autobiographical reflections of senior members of the field, occasional humorous essays and sketches, and even has a section for invited and submitted articles.
The impact of the journal can be seen through the reverberation of a 2009 article on correlative analyses commonly used in neuroimaging studies, which still influences the field. Additionally, a recent special issue of Perspectives, featuring prominent researchers discussing the "Next Big Questions in Psychology," is shaping the future trajectory of the discipline.
Perspectives on Psychological Science provides metrics that showcase the performance of the journal. However, the Association for Psychological Science, of which the journal is a signatory of DORA, recommends against using journal-based metrics for assessing individual scientist contributions, such as for hiring, promotion, or funding decisions. Therefore, the metrics provided by Perspectives on Psychological Science should only be used by those interested in evaluating the journal itself.