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

Health and Risk Communication (57) JMIR Theme Issue: COVID-19 Special Issue (2496)

Published on in Vol 1, No 1 (2021): Jan-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/25242, first published .
The Role of the Canadian Media During the Initial Response to the COVID-19 Pandemic: A Topic Modelling Approach Using Canadian Broadcasting Corporation News Articles

The Role of the Canadian Media During the Initial Response to the COVID-19 Pandemic: A Topic Modelling Approach Using Canadian Broadcasting Corporation News Articles

The Role of the Canadian Media During the Initial Response to the COVID-19 Pandemic: A Topic Modelling Approach Using Canadian Broadcasting Corporation News Articles

Authors of this article:

Janhavi Patel1 Author Orcid Image ;   Harsheev Desai2 Author Orcid Image ;   Ali Okhowat3 Author Orcid Image
Article Authors Cited by (4) Tweetations (6) Metrics

Journals

  1. 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
  2. Schwarz A, Alpers F, Wagner-Olfermann E, Diers-Lawson A. The Global Study of COVID News: Scope, Findings, and Implications of Quantitative Content Analyses of the COVID-19 News Coverage in the First Two Years of the Pandemic. Health Communication 2024;39(8):1568 View
  3. Chandrabhatla A, Narahari A, Horgan T, Patel P, Sturek J, Davis C, Jackson P, Bell T. Machine Learning-based Analysis of Publications Funded by the National Institutes of Health's Initial COVID-19 Pandemic Response. Open Forum Infectious Diseases 2024;11(4) View

Conference Proceedings

  1. Silalahi S, Arini H, Mulyani Y. THE PROCEEDINGS OF THE 5TH INTERNATIONAL CONFERENCE ON MARITIME EDUCATION AND TRAINING (The 5th ICMET) 2021. Topic modelling and sentiment analysis during Covid-19 pandemic response: A systematic review View