2026-05-02T03:47:29Z https://datacatalogue.cessda.eu/oai-pmh/v0/oai

a396551991be02283579b7aa6a19c8d496d2bc278f40716fc67bc84112cf94c0 2025-06-17T03:16:12Z language:enopenaire_data

DDI study level documentation for study 10.7802/2453 Replication Code: Gummer & Oehrlein (2022): "Using Google Trends Data to Learn More About Survey Participation." Social Science Computer Review Replication Code: Gummer & Oehrlein (2022): "Using Google Trends Data to Learn More About Survey Participation." Social Science Computer Review Replication Code: Gummer & Oehrlein (2022): "Using Google Trends Data to Learn More About Survey Participation." Social Science Computer Review 10.7802/245310.7802/245310.7802/245310.7802/2453 Gummer, Tobias Gummer, Tobias Oehrlein, Anne-Sophie Oehrlein, Anne-Sophie GESIS Data Archive for the Social SciencesGESIS Datenarchiv für Sozialwissenschaften 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.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. Free access (with registration) - The research data can be downloaded by registered users.Freier Zugang (mit Registrierung) - Die Forschungsdaten können von allen registrierten Nutzerinnen und Nutzern heruntergeladen werden. http://dbkapps.gesis.org/dbkoai/oai.asp oai:dbk.gesis.org:SDN/10.7802_2453 2023-03-11 ddi:codebook:2_5