Google search data for psychological scientists: a tutorial and best practices

Abstract

Google searches have been described as the most important dataset on the human psyche ever assembled. Google search data—accessible through a tool called Google Trends—can provide new insights on topics as varied as stereotypes and prejudices, political attitudes, religious identity and belief, personality, motivations, psychological well-being, mental health, and culture. Google Trends can generate highly customized datasets: Users can compare the popularity of search terms across most of the world, or access longitudinal data as far back as 2004, and they can do so with high geographical and temporal granularity. Notwithstanding these opportunities, Google Trends has significant limitations. Without appropriate caution, users can easily rely on data that are not meaningful or draw mistaken conclusions. We provide a comprehensive overview and tutorial, covering (a) opportunities of Google Trends for psychological scientists; (b) how Google Trends scores are calculated, how reliable they are, and why some queries might yield low-quality data; (c) instructions with accompanying R code for creating custom datasets beyond what Google Trends provides by default; (d) example analyses for studies that could be done using Google Trends data; (e) an overview of common pitfalls; and (f) recommendations for safeguarding data quality and their interpretation.

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ORCID for Jordan W. Moon: orcid.org/0000-0001-5102-3585

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