2026-04-30T00:06:01Z https://datacatalogue.cessda.eu/oai-pmh/v0/oai

743a0cf43984e34404d1bc7e6ec71ca0bcc52e6e9b052afd2742057a3314511b 2025-06-17T03:17:30Z language:enopenaire_data

DDI study level documentation for study 10.7802/2748 Replication Code: Gummer & Oehrlein (2024): "Using Google Trends Data to Study High-Frequency Search Terms: Evidence for a Reliability-Frequency Continuum." Social Science Computer Review Replication Code: Gummer & Oehrlein (2024): "Using Google Trends Data to Study High-Frequency Search Terms: Evidence for a Reliability-Frequency Continuum." Social Science Computer Review Replication Code: Gummer & Oehrlein (2024): "Using Google Trends Data to Study High-Frequency Search Terms: Evidence for a Reliability-Frequency Continuum." Social Science Computer Review 10.7802/274810.7802/274810.7802/274810.7802/2748 Gummer, Tobias Gummer, Tobias Oehrlein, Anne-Sophie Oehrlein, Anne-Sophie GESIS Data Archive for the Social SciencesGESIS Datenarchiv für Sozialwissenschaften Based on the data and the syntax file, the results reported in the cited article can be replicated. Google Trends (GT) data are increasingly used in the social sciences and adjacent fields. However, previous research on the quality of GT data has raised concerns regarding their reliability. In the present study, we investigated whether reliability differs between low- and high-frequency search terms. In other words, we explored the existence of a reliability-frequency continuum in GT data. Our study adds to previous research by investigating a more comprehensive set of search terms and different aspects of reliability (e.g., differences in relative search volume distributions, correctly identified maxima). For this purpose, we collected samples of GT data for ten high- and two low-frequency search terms. We obtained one real-time sample and 62 non-realtime samples per search term (30 non-realtime samples for low-frequency search terms). Data collection was restricted to search data for Germany. Our data support the existence of a reliability-frequency continuum—low-frequency search terms are subject to greater reliability issues compared to high-frequency search terms. Based on our findings, we have derived practical recommendations for the use of GT data and have outlined future research opportunities.Based on the data and the syntax file, the results reported in the cited article can be replicated. Google Trends (GT) data are increasingly used in the social sciences and adjacent fields. However, previous research on the quality of GT data has raised concerns regarding their reliability. In the present study, we investigated whether reliability differs between low- and high-frequency search terms. In other words, we explored the existence of a reliability-frequency continuum in GT data. Our study adds to previous research by investigating a more comprehensive set of search terms and different aspects of reliability (e.g., differences in relative search volume distributions, correctly identified maxima). For this purpose, we collected samples of GT data for ten high- and two low-frequency search terms. We obtained one real-time sample and 62 non-realtime samples per search term (30 non-realtime samples for low-frequency search terms). Data collection was restricted to search data for Germany. Our data support the existence of a reliability-frequency continuum—low-frequency search terms are subject to greater reliability issues compared to high-frequency search terms. Based on our findings, we have derived practical recommendations for the use of GT data and have outlined future research opportunities. 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_2748 2024-08-30 ddi:codebook:2_5