Community Detection in Google Searches Related to “Coronavirus”

Philip D Waggoner

doi:10.6339/21-jds1001

Abstract

Coronavirus and the COVID-19 pandemic have substantially altered the ways in which people learn, interact, and discover information. In the absence of everyday in-person interaction, how do people self-educate while living in isolation during such times? More specifically, do communities emerge in Google search trends related to coronavirus? Using a suite of network and community detection algorithms, we scrape and mine all Google search trends in America related to an initial search for “coronavirus,” starting with the first Google search on the term (January 16, 2020) to recently (August 11, 2020). Results indicate a near-constant shift in the structure of how people educate themselves on coronavirus. Queries in the earliest days focusing on “Wuhan” and “China”, then shift to “stimulus checks” at the height of the virus in the U.S., and finally shift to queries related to local surges of new cases in later days. A few communities emerge surrounding terms more overtly related to coronavirus (e.g., “cases”, “symptoms”, etc.). Yet, given the shift in related Google queries and the broader information environment, clear community structure for the full search space does not emerge.

Highlights

The impact of COVID-19 on the global society has been striking
In the absence of everyday in-person interaction, how do people self-educate while living in isolation during such times? do communities emerge in Google search trends related to coronavirus? Using a suite of network and community detection algorithms, we scrape and mine all Google search trends in America related to an initial search for “coronavirus,” starting with the first Google search on the term (January 16, 2020) to recently (August 11, 2020)
Though departing from some of the existing research on COVID-19 and online communities and building on recent similar work (Effenberger et al, 2020; Rovetta and Bhagavathula, 2020), we address this question by focusing on the individual level, starting at the place most people start when interested to learn more about any topic: Google

Summary

Introduction

The impact of COVID-19 on the global society has been striking. From isolation and fear of contracting coronavirus to the slowing of many local economies and limitation of in-person interactions, the effects of COVID-19 have threatened the modern flow of life. People across the world are often living and working in isolation, or at least are more separated from local communities than prior to the pandemic. Absent in-person interaction, how do people self-educate and learn about coronavirus?. Despite the still-newness of COVID-19 and coronavirus, there is an impressive amount of extant work on related topics. Much of the research surrounding online behavior and COVID-19 tends to focus on misinformation (Pennycook et al, 2020; Bastani and Bahrami, 2020), fake news (Apuke and Omar, 2020; van der Linden et al, 2020), and smart-phone-enabled selfdiagnosis (Collado-Borrell et al, 2020). Research on COVID-19 and online behavior is becoming increasingly creative and nuanced as the virus wears on, such as exploring online shopping (Laato et al, 2020), binge television watching (Dixit et al, 2020), and changes in sexual behavior (Lehmiller et al, 2020)

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Conclusion