Using Google Trends Data to Learn More About Survey Participation

被引:4
|
作者
Gummer, Tobias [1 ,2 ]
Oehrlein, Anne-Sophie [1 ]
机构
[1] GESIS Leibniz Inst Social Sci, B6,4-5, D-68159 Mannheim, Germany
[2] Univ Mannheim, Sch Social Sci, Mannheim, Germany
关键词
survey participation; nonresponse; google trends data; auxiliary data; digital trace data; search engine data; NONRESPONSE RATES;
D O I
10.1177/08944393221129179
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
As response rates continue to decline, the need to learn more about the survey participation process remains an important task for survey researchers. Search engine data may be one possible source for learning about what information some potential respondents are looking up about a survey when they are making a participation decision. In the present study, we explored the potential of search engine data for learning about survey participation and how it can inform survey design decisions. We drew on freely available Google Trends (GT) data to learn about the use of Google Search with respect to our case study: participation in the Family Research and Demographic Analysis (FReDA) panel survey. Our results showed that some potential respondents were using Google Search to gather information on the FReDA survey. We also showed that the additional data obtained via GT can help survey researchers to discover topics of interest to respondents and geographically stratified search patterns. Moreover, we introduced different approaches for obtaining data via GT, discussed the challenges that come with these data, and closed with practical recommendations on how survey researchers might utilize GT data to learn about survey participation.
引用
收藏
页码:1968 / 1985
页数:18
相关论文
共 50 条
  • [31] Google Internet searches related to inflammatory arthritis: An observational study using Google Trends data
    Akthar, Mumina
    Mason, Kayleigh J.
    Scott, Ian C.
    MUSCULOSKELETAL CARE, 2024, 22 (03)
  • [32] Is Google Trends a quality data source?
    Cebrian, Eduardo
    Domenech, Josep
    APPLIED ECONOMICS LETTERS, 2023, 30 (06) : 811 - 815
  • [33] The measurement errors of google trends data
    Kerry Liu
    Discover Data, 2 (1):
  • [34] Nowcasting and Forecasting Morocco GDP growth using Google Trends data
    Bouayad, Imane
    Zahir, Jihad
    Ez-zetouni, Adil
    IFAC PAPERSONLINE, 2022, 55 (10): : 3280 - 3285
  • [35] Using Google Trends Data to Track Healthcare Use for Hand Osteoarthritis
    Cohen, Samuel A.
    Zhuang, Thompson
    Xiao, Michelle
    Michaud, John B.
    Shapiro, Lauren
    Kamal, Robin N.
    CUREUS JOURNAL OF MEDICAL SCIENCE, 2021, 13 (03)
  • [36] Using Google trends data to assess public understanding on the environmental risks
    Durmusoglu, Zeynep Didem Unutmaz
    HUMAN AND ECOLOGICAL RISK ASSESSMENT, 2017, 23 (08): : 1968 - 1977
  • [37] Forecasting tuberculosis using diabetes-related google trends data
    Frauenfeld, Leonie
    Nann, Dominik
    Sulyok, Zita
    Feng, You-Shan
    Sulyok, Mihaly
    PATHOGENS AND GLOBAL HEALTH, 2020, 114 (05) : 236 - 241
  • [38] Forecasting British Tourist Inflows to Portugal Using Google Trends Data
    Dinis, Gorete
    Costa, Carlos
    Pacheco, Osvaldo
    TOURISM, CULTURE AND HERITAGE IN A SMART ECONOMY, 2017, : 483 - 496
  • [39] Clinicians learn less and less about more and more until they know nothing about everything; researchers learn more and more about less and less until they know everything about nothing: Discuss
    Aitken, Kenneth John
    BEHAVIORAL AND BRAIN SCIENCES, 2012, 35 (05) : 358 - 359
  • [40] Is there more to learn about the epidemiology of lung cancer?
    Samet, Jonathan Matthew
    EUROPEAN JOURNAL OF EPIDEMIOLOGY, 2016, 31 (12) : 1159 - 1160