Google Trends as a Method to predict new COVID-19 Cases and socio-psychological Consequences of the Pandemic

Abstract: Background: Understanding how people react to the COVID-19 crisis, and what the consequences are of the COVID-19 pandemic is key to enable public health and other agencies to develop optimal intervention strategies. Objective: Because the timely identification of new cases of infection has proven to be the key to timely respond to the spread of infection within a particular region, we have developed a method that can detect and predict the emergence of new cases of COVID-19 at an early stage. Further, this method can give useful insights into a family’s life during the pandemic and give the prediction of birth rates. Methods: The basic methodological concept of our approach is to monitor the digital trace of language searches with the Google Trends analytical tool (GT). We divided the keyword frequency for selected words giving us a search frequency index and then compared searches with official statistics to prove the significations of results. Results: 1.) Google Trends tools are

Angaben zum Objekt

• Standort: Deutsche Nationalbibliothek Frankfurt am Main
• Umfang: Online-Ressource
• Sprache: Englisch
• Anmerkungen: Veröffentlichungsversion ; begutachtet (peer reviewed) ; In: Athens Journal of Mediterranean Studies ; 7 (2021) ; 1-25

Beteiligte, Orts- und Zeitangaben

• Ereignis: Veröffentlichung
• (wo): Mannheim
• (wer): SSOAR, GESIS – Leibniz-Institut für Sozialwissenschaften e.V.
• (wann): 2021
• Urheber: Juric, Tado

Weitere Informationen

• URN: urn:nbn:de:0168-ssoar-73838-7
• Rechteinformation: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
• Letzte Aktualisierung: 25.03.2025, 13:50 MEZ