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

JMIR Theme Issue: COVID-19 Special Issue (2548) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1902) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1132) Outbreak and Pandemic Preparedness and Management (1819) Infectious Diseases (non-STD/STI) (1712) Infodemiology and Infoveillance (1553)

Published on in Vol 23, No 7 (2021): July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/28615, first published .
Emergency Physician Twitter Use in the COVID-19 Pandemic as a Potential Predictor of Impending Surge: Retrospective Observational Study

Emergency Physician Twitter Use in the COVID-19 Pandemic as a Potential Predictor of Impending Surge: Retrospective Observational Study

Emergency Physician Twitter Use in the COVID-19 Pandemic as a Potential Predictor of Impending Surge: Retrospective Observational Study

Authors of this article:

Colton Margus1, 2 Author Orcid Image ;   Natasha Brown1, 2 Author Orcid Image ;   Attila J Hertelendy1, 3 Author Orcid Image ;   Michelle R Safferman4, 5 Author Orcid Image ;   Alexander Hart1, 2 Author Orcid Image ;   Gregory R Ciottone1, 2 Author Orcid Image
Article Authors Cited by (15) Tweetations (4) Metrics

Journals

  1. Liew T, Lee C. Examining the Utility of Social Media in COVID-19 Vaccination: Unsupervised Learning of 672,133 Twitter Posts. JMIR Public Health and Surveillance 2021;7(11):e29789 View
  2. MacLeod S, Singh N, Boyd C. The Unclear Role of the Physician on Social Media During the COVID-19 Pandemic. Comment on “Emergency Physician Twitter Use in the COVID-19 Pandemic as a Potential Predictor of Impending Surge: Retrospective Observational Study”. Journal of Medical Internet Research 2022;24(3):e34870 View
  3. Nakagawa K, Yang N, Wilson M, Yellowlees P. Twitter Usage Among Physicians From 2016 to 2020: Algorithm Development and Longitudinal Analysis Study. Journal of Medical Internet Research 2022;24(9):e37752 View
  4. Khan S, Biswas M, Shah Z. Longitudinal analysis of behavioral factors and techniques used to identify vaccine hesitancy among Twitter users: Scoping review. Human Vaccines & Immunotherapeutics 2023;19(3) View
  5. Mazzeffi M, Strickland L, Coffman Z, Miller B, Hilton E, Kohan L, Keneally R, McNaull P, Elkassabany N, Haunschild R. Cross sectional study of Twitter (X) use among academic anesthesiology departments in the United States. PLOS ONE 2024;19(2):e0298741 View
  6. Weber S, Wyszynski M, Godefroid M, Plattfaut R, Niehaves B. How do medical professionals make sense (or not) of AI? A social-media-based computational grounded theory study and an online survey. Computational and Structural Biotechnology Journal 2024;24:146 View
  7. Kirpekar M, Kars M, Mariano E, Patel A. The Professional Use of Social Media in Anesthesiology: Developing a Digital Presence Is as Easy as ABCDE. Anesthesia & Analgesia 2024;139(1):238 View
  8. Chepo M, Martin S, Déom N, Khalid A, Vindrola-Padros C. Twitter Analysis of Health Care Workers’ Sentiment and Discourse Regarding Post–COVID-19 Condition in Children and Young People: Mixed Methods Study. Journal of Medical Internet Research 2024;26:e50139 View
  9. Qureshi N, Huilgol S, Berdahl C, Cohen C, Mendel P, Fischer S. Understanding uptake of information about innovations among emergency department clinicians during the COVID‐19 pandemic. JACEP Open 2024;5(4):e13243 View
  10. Helgeson S, Mudgalkar R, Jacobs K, Lee A, Sanghavi D, Moreno Franco P, Brooks I. Association Between X/Twitter and Prescribing Behavior During the COVID-19 Pandemic: Retrospective Ecological Study. JMIR Infodemiology 2024;4:e56675 View
  11. Wilson F, Stimpson J, Young M, Bustamante A, Ponce N, Ortega A. Mis- and disinformation and perceptions of healthcare policy among Latinos in the USA: protocol for a multi-method social media sentiment analysis study. BMJ Open 2025;15(7):e096465 View

Books/Policy Documents

  1. Dhir K, Singh P, Dwivedi Y, Sawhney S, Sawhney R. Co-creating for Context in the Transfer and Diffusion of IT. View
  2. Safa R, Edalatpanah S, Sorourkhah A. Deep Learning in Personalized Healthcare and Decision Support. View

Conference Proceedings

  1. Nirbhik N, Kumar S. 2023 International Conference on Advanced Computing Technologies and Applications (ICACTA). Integrating Text and Emoticons for Detecting Extremist Affiliations on Twitter using Deep Learning View
  2. Nirbhik N, Kumar S. 2023 5th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N). Navigating the Sentiment Analysis Landscape: Methodologies and Use Cases in Social Media Analysis View