未开发的潜力:在线调查实验中设计的数字痕迹数据

IF 6.5 2区 社会学 Q1 SOCIAL SCIENCES, MATHEMATICAL METHODS Sociological Methods & Research Pub Date : 2024-08-09 DOI:10.1177/00491241241268770
Erin Macke, Claire Daviss, Emma Williams-Baron
{"title":"未开发的潜力:在线调查实验中设计的数字痕迹数据","authors":"Erin Macke, Claire Daviss, Emma Williams-Baron","doi":"10.1177/00491241241268770","DOIUrl":null,"url":null,"abstract":"Researchers have developed many uses for digital trace data, yet most online survey experiments continue to rely on attitudinal rather than behavioral measures. We argue that researchers can collect digital trace data during online survey experiments with relative ease, at modest costs, and to substantial benefit. Because digital trace data unobtrusively measure survey participants’ behaviors, they can be used to analyze digital outcomes of theoretical and empirical interest, while reducing the risk of social desirability bias. We demonstrate the feasibility and utility of collecting digital trace data during online survey experiments through two original studies. In both, participants evaluated interactive digital resumes designed to track participants’ clicks, mouse movements, and time spent on the resumes. This novel approach allowed us to better understand participants’ search for information and cognitive processing in hiring decisions. There is immense, untapped potential value in collecting digital trace data during online survey experiments and using it to address important sociological research questions.","PeriodicalId":21849,"journal":{"name":"Sociological Methods & Research","volume":null,"pages":null},"PeriodicalIF":6.5000,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Untapped Potential: Designed Digital Trace Data in Online Survey Experiments\",\"authors\":\"Erin Macke, Claire Daviss, Emma Williams-Baron\",\"doi\":\"10.1177/00491241241268770\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Researchers have developed many uses for digital trace data, yet most online survey experiments continue to rely on attitudinal rather than behavioral measures. We argue that researchers can collect digital trace data during online survey experiments with relative ease, at modest costs, and to substantial benefit. Because digital trace data unobtrusively measure survey participants’ behaviors, they can be used to analyze digital outcomes of theoretical and empirical interest, while reducing the risk of social desirability bias. We demonstrate the feasibility and utility of collecting digital trace data during online survey experiments through two original studies. In both, participants evaluated interactive digital resumes designed to track participants’ clicks, mouse movements, and time spent on the resumes. This novel approach allowed us to better understand participants’ search for information and cognitive processing in hiring decisions. There is immense, untapped potential value in collecting digital trace data during online survey experiments and using it to address important sociological research questions.\",\"PeriodicalId\":21849,\"journal\":{\"name\":\"Sociological Methods & Research\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":6.5000,\"publicationDate\":\"2024-08-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Sociological Methods & Research\",\"FirstCategoryId\":\"90\",\"ListUrlMain\":\"https://doi.org/10.1177/00491241241268770\",\"RegionNum\":2,\"RegionCategory\":\"社会学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"SOCIAL SCIENCES, MATHEMATICAL METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sociological Methods & Research","FirstCategoryId":"90","ListUrlMain":"https://doi.org/10.1177/00491241241268770","RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"SOCIAL SCIENCES, MATHEMATICAL METHODS","Score":null,"Total":0}
引用次数: 0

摘要

研究人员已经开发了许多数字跟踪数据的用途,但大多数在线调查实验仍然依赖于态度测量而非行为测量。我们认为,在在线调查实验中,研究人员可以相对轻松地收集数字跟踪数据,成本不高,却能获得巨大收益。由于数字跟踪数据可以不引人注意地测量调查参与者的行为,因此可以用来分析理论和实证研究中感兴趣的数字结果,同时降低社会可取性偏差的风险。我们通过两项原创研究证明了在在线调查实验中收集数字跟踪数据的可行性和实用性。在这两项研究中,参与者对互动式数字简历进行了评估,旨在跟踪参与者的点击、鼠标移动以及在简历上花费的时间。这种新颖的方法使我们能够更好地了解参与者在招聘决策中的信息搜索和认知处理过程。在在线调查实验中收集数字跟踪数据,并将其用于解决重要的社会学研究问题,具有巨大的、尚未开发的潜在价值。
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
Untapped Potential: Designed Digital Trace Data in Online Survey Experiments
Researchers have developed many uses for digital trace data, yet most online survey experiments continue to rely on attitudinal rather than behavioral measures. We argue that researchers can collect digital trace data during online survey experiments with relative ease, at modest costs, and to substantial benefit. Because digital trace data unobtrusively measure survey participants’ behaviors, they can be used to analyze digital outcomes of theoretical and empirical interest, while reducing the risk of social desirability bias. We demonstrate the feasibility and utility of collecting digital trace data during online survey experiments through two original studies. In both, participants evaluated interactive digital resumes designed to track participants’ clicks, mouse movements, and time spent on the resumes. This novel approach allowed us to better understand participants’ search for information and cognitive processing in hiring decisions. There is immense, untapped potential value in collecting digital trace data during online survey experiments and using it to address important sociological research questions.
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
CiteScore
16.30
自引率
3.20%
发文量
40
期刊介绍: Sociological Methods & Research is a quarterly journal devoted to sociology as a cumulative empirical science. The objectives of SMR are multiple, but emphasis is placed on articles that advance the understanding of the field through systematic presentations that clarify methodological problems and assist in ordering the known facts in an area. Review articles will be published, particularly those that emphasize a critical analysis of the status of the arts, but original presentations that are broadly based and provide new research will also be published. Intrinsically, SMR is viewed as substantive journal but one that is highly focused on the assessment of the scientific status of sociology. The scope is broad and flexible, and authors are invited to correspond with the editors about the appropriateness of their articles.
期刊最新文献
Sharing Big Video Data: Ethics, Methods, and Technology Dynamics of Health Expectancy: An Introduction to the Multiple Multistate Method (MMM) Seeded Topic Models in Digital Archives: Analyzing Interpretations of Immigration in Swedish Newspapers, 1945–2019 A Primer on Deep Learning for Causal Inference Untapped Potential: Designed Digital Trace Data in Online Survey Experiments
×
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