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Content analysis and characterization of medical tweets during the early Covid-19 pandemic
Ross Prager; Michael Pratte; Rudy R Unni; Sudarshan Bala; Nicholas Ng Fat Hing; Kay Wu; Trevor A McGrath; Adam Thomas; Laura Hilary Thompson; Julia Hajjar; Brent Thoma; Philippe Rola; Alan Karovitch; Kwadwo Kyeremanteng.
Affiliation
  • Ross Prager; University of Ottawa
  • Michael Pratte; University of Ottawa
  • Rudy R Unni; University of Ottawa
  • Sudarshan Bala; McMaster University
  • Nicholas Ng Fat Hing; University of Ottawa
  • Kay Wu; McMaster University
  • Trevor A McGrath; University of Ottawa
  • Adam Thomas; University of British Columbia
  • Laura Hilary Thompson; Ottawa Hospital Research Institute
  • Julia Hajjar; Ottawa Hospital Research Institute
  • Brent Thoma; University of Saskatchewan
  • Philippe Rola; Santa Cabrini Hospital
  • Alan Karovitch; University of Ottawa
  • Kwadwo Kyeremanteng; University of Ottawa
Preprint in English | medRxiv | ID: ppmedrxiv-20248712
Journal article
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ABSTRACT
ObjectiveThe 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, ParticipantsTwitter 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. ResultsThe search yielded 8541 original tweets from 4104 contributors. The number of tweets in each content category were 1557 other Covid-19 (18{middle dot}2%), 1190 emotional impact (13{middle dot}9%), 1122 FOAM resources (13{middle dot}1%), 1111 policy discussion (13{middle dot}0%), 928 advice (10{middle dot}9%), 873 learned experience (10{middle dot}2%), 424 non-Covid-19 (5{middle dot}0%), 410 podcast or video (4{middle dot}8%), 304 editorials (3{middle dot}6%), 275 original research (3{middle dot}2%), 245 public health (2{middle dot}9%), 83 refuting false information (1{middle dot}0%), and 19 blatantly false (0{middle dot}2%). ConclusionsEarly 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.
License
cc_by_nc
Full text: Available Collection: Preprints Database: medRxiv Type of study: Experimental_studies / Qualitative research / Rct Language: English Year: 2020 Document type: Preprint
Full text: Available Collection: Preprints Database: medRxiv Type of study: Experimental_studies / Qualitative research / Rct Language: English Year: 2020 Document type: Preprint
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