Untapped Potential: Designed Digital Trace Data in Online Survey Experiments

被引:0
|
作者
Macke, Erin [1 ]
Daviss, Claire [1 ]
Williams-Baron, Emma [1 ]
机构
[1] Stanford Univ, Dept Sociol, Stanford, CA 94305 USA
基金
美国国家科学基金会;
关键词
digital trace data; survey design; computational social science; paradata; online survey experiments; DIFFUSION DECISION-MODEL; BIG DATA; INFORMED-CONSENT; SELF-REPORT; INFORMATION; CHALLENGES; PARADATA; BEHAVIOR; ISSUES; DISCRIMINATION;
D O I
10.1177/00491241241268770
中图分类号
O1 [数学]; C [社会科学总论];
学科分类号
03 ; 0303 ; 0701 ; 070101 ;
摘要
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.
引用
收藏
页数:41
相关论文
共 50 条
  • [31] UNTAPPED POTENTIAL: A CRITICAL ANALYSIS OF THE UTILITY OF DATA MANAGEMENT PLANS IN FACILITATING DATA SHARING
    Carlson, Jake
    JOURNAL OF RESEARCH ADMINISTRATION, 2023, 54 (03) : 93 - 113
  • [32] TaskRouter: A Newly Designed Online Data Processing Framework
    Gu, Minhao
    Zhu, Kejun
    Li, Fei
    Shen, Wei
    2016 IEEE-NPSS REAL TIME CONFERENCE (RT), 2016,
  • [33] EVENT TIMING AND RECORDING IN DIGITAL FORMAT FOR ONLINE EXPERIMENTS
    BLOOMFIELD, RJ
    ERGONOMICS, 1978, 21 (05) : 389 - 392
  • [34] Challenges of Digital Building Data Usage with a Focus on the Digital Documentation of Heritage Buildings-Results from an Online Survey
    Khalil, Ahmed
    Stravoravdis, Spyridon
    HERITAGE, 2022, 5 (04): : 3220 - 3259
  • [35] Digital trace Data: the end of empirical Sociology?
    Sedlacek, Jakub
    SOCIOLOGICKY CASOPIS-CZECH SOCIOLOGICAL REVIEW, 2020, 56 (04): : 471 - 490
  • [36] Unlocking the Untapped Potential of Video Game Data: A Case Study of Aim Trainers
    Rejthar, Jan
    VIDEOGAME SCIENCES AND ARTS, VJ 2023, 2024, 1984 : 315 - 321
  • [37] On kernel nonparametric regression designed for complex survey data
    Harms, Torsten
    Duchesne, Pierre
    METRIKA, 2010, 72 (01) : 111 - 138
  • [38] The analysis of designed experiments and longitudinal data by using smoothing splines
    Verbyla, AP
    Cullis, BR
    Kenward, MG
    Welham, SJ
    JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS, 1999, 48 : 269 - 300
  • [39] Improving Data Explainability in Analysis of Designed Computer Simulation Experiments
    Xie, Shengkun
    Lawniczak, Anna
    Hao, Junlin
    Gan, Chong
    2019 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (IEEE SSCI 2019), 2019, : 1486 - 1493
  • [40] On kernel nonparametric regression designed for complex survey data
    Torsten Harms
    Pierre Duchesne
    Metrika, 2010, 72 : 111 - 138