Abstract

The article is focused on a detailed micro-study describing changes in the behaviour of the authors in three months before and during the COVID-19 pandemic. The study is based on data from Google Location Service. Despite the fact it evaluates only three people and the study cannot be sufficiently representative, it is a unique example of possible data processing at such a level of accuracy. The most significant changes in the behaviour of authors before and during the COVID-19 quarantine are described and interpreted in detail. Another purpose of the article is to point out the possibilities of analytical processing of Google Location while being aware of personal data protection issues. The authors recognize that by visualizing the real motion data, one partially discloses their privacy, but one considers it very valuable to show how detailed data Google collects about the population and how such data can be used effectively.

Highlights

  • After the sudden approach of COVID-19 pandemic to our lives, people have had to adjust daily routines according to nation-wide restrictions and anti-epidemic measures

  • In Czechia, such data are used in the so-called “smart quarantine”, which is based on the visualization of individual mobile phone data to for detect the movement of infected people

  • On 3 April 2020, Google released a new service, COVID-19 Community Mobility Reports (Google LLC, 2020), in response to requests from official institutions to provide at least anonymized data and the behaviour of Google Location users

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Summary

A Case Study on the Impact of COVID-19 Using Personal Google Locations Data

Vít Pászto, Palacký University Olomouc, Czech Republic & Moravian Business College Olomouc, Czech Republic Jaroslav Burian, Palacký University Olomouc, Czech Republic & Moravian Business College Olomouc, Czech Republic Karel Macků, Palacký University Olomouc, Czech Republic

INTRODUCTION
DATA AND METHODS
PERSONALISED ANALYSES OF GOOGLE LOCATION DATA
DISCUSSION
CONCLUSION
Full Text
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