This paper is in the following e-collection/theme issue:

Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1015) JMIR Theme Issue: COVID-19 Special Issue (2394) Infodemiology and Infoveillance (1278) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1484) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1573) Outbreak and Pandemic Preparedness and Management (1679) Quality/Credibility of eHealth Information and Trust Issues (492) Mass Media/Social Media Communication and Campaigns (450) Infoveillance and Social Listening (181) Information Demand (31)

Published on in Vol 7, No 12 (2021): December

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/31834, first published .
The Spread of COVID-19 Crisis Communication by German Public Authorities and Experts on Twitter: Quantitative Content Analysis

The Spread of COVID-19 Crisis Communication by German Public Authorities and Experts on Twitter: Quantitative Content Analysis

The Spread of COVID-19 Crisis Communication by German Public Authorities and Experts on Twitter: Quantitative Content Analysis

Authors of this article:

Larissa S Drescher1 Author Orcid Image ;   Jutta Roosen1, 2 Author Orcid Image ;   Katja Aue1 Author Orcid Image ;   Kerstin Dressel3 Author Orcid Image ;   Wiebke Schär3 Author Orcid Image ;   Anne Götz3 Author Orcid Image
Article Authors Cited by (11) Tweetations (5) Metrics

Journals

  1. Balakina J. COVID-19 pandemic in Germany: information campaign, media, society. Baltic Region 2022;14(3):83 View
  2. Chin H, Lima G, Shin M, Zhunis A, Cha C, Choi J, Cha M. User-Chatbot Conversations During the COVID-19 Pandemic: Study Based on Topic Modeling and Sentiment Analysis. Journal of Medical Internet Research 2023;25:e40922 View
  3. Su Z, Zhang H, McDonnell D, Ahmad J, Cheshmehzangi A, Yuan C. Crisis communication strategies for health officials. Frontiers in Public Health 2022;10 View
  4. Etienne D, Archambault P, Aziaka D, Chipenda-Dansokho S, Dubé E, Fallon C, Hakim H, Kindrachuk J, Krecoum D, MacDonald S, Ndjaboue R, Noubi M, Paquette J, Parent E, Witteman H. A Personalized Avatar-Based Web Application to Help People Understand How Social Distancing Can Reduce the Spread of COVID-19: Cross-sectional, Observational, Pre-Post Study. JMIR Formative Research 2023;7:e38430 View
  5. Drescher L, Roosen J, Aue K, Dressel K, Schär W, Götz A. Emotionalität in der COVID-19-Krisenkommunikation von Behörden und unabhängigen Expert*innen auf Twitter. Bundesgesundheitsblatt - Gesundheitsforschung - Gesundheitsschutz 2023;66(6):689 View
  6. Zurro-Antón N, Moreno Á, Humanes M. CERC como modelo de investigación en crecimiento: análisis de su aplicación en las estrategias de comunicación de emergencias sanitarias en la última década. Estudios sobre el Mensaje Periodístico 2023;29(2):395 View
  7. Kresovich A, Norris A, Carter C, Kim Y, Kostygina G, Emery S. Deciphering Influence on Social Media: A Comparative Analysis of Influential Account Detection Metrics in the Context of Tobacco Promotion. Social Media + Society 2024;10(1) View
  8. Gyftopoulos S, Drosatos G, Fico G, Pecchia L, Kaldoudi E. Analysis of Pharmaceutical Companies’ Social Media Activity during the COVID-19 Pandemic and Its Impact on the Public. Behavioral Sciences 2024;14(2):128 View
  9. Mohamed Nour M, Kisa A. Political Leaders’ Communication Strategies during COVID-19 in Highly Infected Countries: A Scoping Review. Healthcare 2024;12(6):607 View
  10. Oliveira E, Nascimento A, Ferreira Junior W, Albuquerque U, Limongi R. How does prestige bias affect information recall during a pandemic?. PLOS ONE 2024;19(5):e0303512 View

Books/Policy Documents

  1. Gyftopoulos S, Drosatos G, Pecchia L, Fico G, Kaldoudi E. MEDICON’23 and CMBEBIH’23. View