Google-Search Data for Psychological Scientists: A Tutorial and Best Practices
Jordan W. Moon & Michael Barlev
What the paper says
Google searches have been described as the most important data set 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 data sets: 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 data sets 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.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.