The measurement errors of google trends data

Abstract

AbstractGoogle Trends is a popular data source that has been utilized in hundreds of studies across various fields, including information technology, business, economics, healthcare, and political science. While several previous research has addressed sampling error issues, this article focuses on the measurement errors resulting from changes in Google Trends' data collection method. By examining key phrases such as ‘covid-19,’ ‘decoupling China,’ and ‘debt trap diplomacy,’ this article reveals that, after 2022 when the data collection method was updated, Google Trends generates search results for terms that were not yet coined or yields too few results. These ‘strange’ search results indicate the presence of measurement errors in Google Trends data. Scholars are advised to validate the contents of Google Trends data through additional steps. In particular, authors in fields like business, economics, and healthcare are encouraged to replicate their research conducted before 2022 to assess the forecasting errors arising from the new data sets retrieved after that period.