争分夺秒:使用响应时间作为自治调查关注度的代理

IF 4.7 2区 社会学 Q1 POLITICAL SCIENCE Political Analysis Pub Date : 2021-09-15 DOI:10.1017/pan.2021.32
Blair Read, L. Wolters, Adam J. Berinsky
{"title":"争分夺秒:使用响应时间作为自治调查关注度的代理","authors":"Blair Read, L. Wolters, Adam J. Berinsky","doi":"10.1017/pan.2021.32","DOIUrl":null,"url":null,"abstract":"Abstract Internet-based surveys have expanded public opinion data collection at the expense of monitoring respondent attentiveness, potentially compromising data quality. Researchers now have to evaluate attentiveness ex-post. We propose a new proxy for attentiveness—response-time attentiveness clustering (RTAC)—that uses dimension reduction and an unsupervised clustering algorithm to leverage variation in response time between respondents and across questions. We advance the literature theoretically arguing that the existing dichotomous classification of respondents as fast or attentive is insufficient and neglects slow and inattentive respondents. We validate our theoretical classification and empirical strategy against commonly used proxies for survey attentiveness. In contrast to other methods for capturing attentiveness, RTAC allows researchers to collect attentiveness data unobtrusively without sacrificing space on the survey instrument.","PeriodicalId":48270,"journal":{"name":"Political Analysis","volume":"30 1","pages":"550 - 569"},"PeriodicalIF":4.7000,"publicationDate":"2021-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Racing the Clock: Using Response Time as a Proxy for Attentiveness on Self-Administered Surveys\",\"authors\":\"Blair Read, L. Wolters, Adam J. Berinsky\",\"doi\":\"10.1017/pan.2021.32\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract Internet-based surveys have expanded public opinion data collection at the expense of monitoring respondent attentiveness, potentially compromising data quality. Researchers now have to evaluate attentiveness ex-post. We propose a new proxy for attentiveness—response-time attentiveness clustering (RTAC)—that uses dimension reduction and an unsupervised clustering algorithm to leverage variation in response time between respondents and across questions. We advance the literature theoretically arguing that the existing dichotomous classification of respondents as fast or attentive is insufficient and neglects slow and inattentive respondents. We validate our theoretical classification and empirical strategy against commonly used proxies for survey attentiveness. In contrast to other methods for capturing attentiveness, RTAC allows researchers to collect attentiveness data unobtrusively without sacrificing space on the survey instrument.\",\"PeriodicalId\":48270,\"journal\":{\"name\":\"Political Analysis\",\"volume\":\"30 1\",\"pages\":\"550 - 569\"},\"PeriodicalIF\":4.7000,\"publicationDate\":\"2021-09-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Political Analysis\",\"FirstCategoryId\":\"90\",\"ListUrlMain\":\"https://doi.org/10.1017/pan.2021.32\",\"RegionNum\":2,\"RegionCategory\":\"社会学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"POLITICAL SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Political Analysis","FirstCategoryId":"90","ListUrlMain":"https://doi.org/10.1017/pan.2021.32","RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"POLITICAL SCIENCE","Score":null,"Total":0}
引用次数: 9

摘要

基于互联网的调查扩大了民意数据的收集,但牺牲了对被调查者注意力的监测,这可能会损害数据质量。研究人员现在必须评估事后的注意力。我们提出了一种新的注意力代理-响应时间注意力聚类(RTAC) -它使用降维和无监督聚类算法来利用受访者之间和跨问题的响应时间变化。我们从理论上提出,现有的快速或注意力二分法对被调查者的分类是不充分的,并且忽略了缓慢和注意力不集中的被调查者。我们验证了我们的理论分类和经验策略,反对常用的调查注意力代理。与其他捕获注意力的方法相比,RTAC允许研究人员在不牺牲调查仪器空间的情况下不显眼地收集注意力数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Racing the Clock: Using Response Time as a Proxy for Attentiveness on Self-Administered Surveys
Abstract Internet-based surveys have expanded public opinion data collection at the expense of monitoring respondent attentiveness, potentially compromising data quality. Researchers now have to evaluate attentiveness ex-post. We propose a new proxy for attentiveness—response-time attentiveness clustering (RTAC)—that uses dimension reduction and an unsupervised clustering algorithm to leverage variation in response time between respondents and across questions. We advance the literature theoretically arguing that the existing dichotomous classification of respondents as fast or attentive is insufficient and neglects slow and inattentive respondents. We validate our theoretical classification and empirical strategy against commonly used proxies for survey attentiveness. In contrast to other methods for capturing attentiveness, RTAC allows researchers to collect attentiveness data unobtrusively without sacrificing space on the survey instrument.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Political Analysis
Political Analysis POLITICAL SCIENCE-
CiteScore
8.80
自引率
3.70%
发文量
30
期刊介绍: Political Analysis chronicles these exciting developments by publishing the most sophisticated scholarship in the field. It is the place to learn new methods, to find some of the best empirical scholarship, and to publish your best research.
期刊最新文献
Assessing Performance of Martins's and Sampson's Formulae for Calculation of LDL-C in Indian Population: A Single Center Retrospective Study. On Finetuning Large Language Models Explaining Recruitment to Extremism: A Bayesian Hierarchical Case–Control Approach Implementation Matters: Evaluating the Proportional Hazard Test’s Performance Face Detection, Tracking, and Classification from Large-Scale News Archives for Analysis of Key Political Figures
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1