The (mis)use of Google Trends data in the social sciences - A systematic review, critique, and recommendations

IF 3.2 2区社会学 Q1 SOCIOLOGY

Social Science Research Pub Date : 2025-02-01 DOI:10.1016/j.ssresearch.2024.103099

Johanna Hölzl, Florian Keusch, Christoph Sajons

{"title":"The (mis)use of Google Trends data in the social sciences - A systematic review, critique, and recommendations","authors":"Johanna Hölzl, Florian Keusch, Christoph Sajons","doi":"10.1016/j.ssresearch.2024.103099","DOIUrl":null,"url":null,"abstract":"<div><div>Researchers increasingly use aggregated search data from Google Trends to study a wide range of phenomena. Although this new data source possesses some important practical and methodological benefits, it also carries substantial challenges with respect to internal validity, reliability, and generalizability. In this paper, we describe and assess the existing applied research with Google Trends data in the social sciences. We conduct a systematic literature review of 360 studies using Google Trends data to (1) illustrate habits and trends and (2) examine whether and how researchers take the identified challenges into account. The results show that the large majority of the literature fails to test the internal validity of their Google Trends measure, does not consider whether their data are reliable across samples, and does not discuss the generalizability of their results. We conclude by stating practical recommendations that will help researchers to address these issues and properly work with Google Trends data.</div></div>","PeriodicalId":48338,"journal":{"name":"Social Science Research","volume":"126 ","pages":"Article 103099"},"PeriodicalIF":3.2000,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Social Science Research","FirstCategoryId":"90","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0049089X24001212","RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"SOCIOLOGY","Score":null,"Total":0}

引用次数: 0

Abstract

Researchers increasingly use aggregated search data from Google Trends to study a wide range of phenomena. Although this new data source possesses some important practical and methodological benefits, it also carries substantial challenges with respect to internal validity, reliability, and generalizability. In this paper, we describe and assess the existing applied research with Google Trends data in the social sciences. We conduct a systematic literature review of 360 studies using Google Trends data to (1) illustrate habits and trends and (2) examine whether and how researchers take the identified challenges into account. The results show that the large majority of the literature fails to test the internal validity of their Google Trends measure, does not consider whether their data are reliable across samples, and does not discuss the generalizability of their results. We conclude by stating practical recommendations that will help researchers to address these issues and properly work with Google Trends data.

查看原文本刊更多论文

求助全文

约1分钟内获得全文求助全文

来源期刊

Social Science Research SOCIOLOGY-

CiteScore

4.30

自引率

4.00%

发文量

审稿时长

65 days

期刊介绍： Social Science Research publishes papers devoted to quantitative social science research and methodology. The journal features articles that illustrate the use of quantitative methods in the empirical solution of substantive problems, and emphasizes those concerned with issues or methods that cut across traditional disciplinary lines. Special attention is given to methods that have been used by only one particular social science discipline, but that may have application to a broader range of areas.