Maximum generable interest: A universal standard for Google Trends search queries

Abstract

The coronavirus or COVID-19 pandemic represents a health event with far-reaching global consequences, triggering a strong search interest in related topics on the Internet worldwide. The use of search engine data has become commonplace in research, but a universal standard for comparing different works is desirable to simplify the comparison. The coronavirus pandemic's enormous impact and media coverage have triggered an exceptionally high search interest. Consequently, the maximum generable interest (MGI) on coronavirus is proposed as a universal reference for objectifying and comparing relative search interest in the future. This search interest can be explored with search engine data such as Google Trends data. Additional standards for medium and low search volumes can also be used to reflect the search interest of topics at different levels. Size standards, such as reference to MGI, may help make research more comparable and better evaluate relative search volumes. This study presents a framework for this purpose using the example of stroke.

Keywords: Google Trends; Infodemiology; Infoveillance; Maximum generable interest; Search engine data; Universal reference.

Fig. 1

Relative weekly search interest in search topics worldwide as indicated according to Google Trends data with “coronavirus” (A) as a reference or relative search interest for one topic with different references as indicated (B).

Fig. 2

Topic “stroke” as example of relative weekly search interest in search topics worldwide according to Google Trends data with reference “diabetes” adapted to level of relative search interest in “stroke” and converted to references “YouTube” and “coronavirus” as indicated.