Content analysis and characterization of medical tweets during the early Covid-19 pandemic

  1. Ross Prager
  2. Michael Pratte
  3. Rudy R. Unni
  4. Sudarshan Bala
  5. Nicholas Ng Fat Hing
  6. Kay Wu
  7. Trevor A. McGrath
  8. Adam Thomas
  9. Laura Hilary Thompson
  10. Julia Hajjar
  11. Brent Thoma
  12. Philippe Rola
  13. Alan Karovitch
  14. Matthew DF McInnes
  15. Kwadwo Kyeremanteng
1 evaluations Published on
Read the full article Related papers
This article on Sciety

Abstract

Objective

The novel coronavirus disease 2019 (Covid-19) has infected millions worldwide and impacted the lives of many folds more. Many clinicians share new Covid-19 related resources, research, and ideas within the online Free Open Access to Medical Education (FOAM) community of practice. This study provides a detailed content and contributor analysis of Covid-19 related tweets among the FOAM community.

Design, Setting, Participants

Twitter was searched from November 1st, 2019 to March 21st, 2020 for English tweets discussing Covid-19 in the FOAM community. Tweets were classified into one of 13 pre-specified content categories: original research, editorials, FOAM resource, public health, podcast or video, learned experience, refuting false information, policy discussion, emotional impact, blatantly false information, other Covid-19, and non-Covid-19. Further analysis of linked original research and FOAM resources was performed. 1000 randomly selected contributor profiles and those deemed to have contributed false information were analyzed.

Results

The search yielded 8541 original tweets from 4104 contributors. The number of tweets in each content category were: 1557 other Covid-19 (18·2%), 1190 emotional impact (13·9%), 1122 FOAM resources (13·1%), 1111 policy discussion (13·0%), 928 advice (10·9%), 873 learned experience (10·2%), 424 non-Covid-19 (5·0%), 410 podcast or video (4·8%), 304 editorials (3·6%), 275 original research (3·2%), 245 public health (2·9%), 83 refuting false information (1·0%), and 19 blatantly false (0·2%).

Conclusions

Early in the Covid-19 pandemic, the FOAM community used Twitter to share Covid-19 learned experiences, online resources, crowd-sourced advice, research, and to discuss the emotional impact of Covid-19. Twitter also provided a forum for post-publication peer review of new research. Sharing blatantly false information within this community was infrequent. This study highlights several potential benefits from engaging with the FOAM community on Twitter.

Related articles

Related articles are currently not available for this article.