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Characterization of the #Radiology Twitter Conversation During the Global COVID-19 Pandemic

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Abstract

Objective: To assess the #Radiology conversation on Twitter social media platform during the COVID-19 pandemic. Materials and Methods: From February 1 to December 31, 2020, all tweets with a #Radiology hashtag were identified using the healthcare social media analytics tool, Symplur Signals. Data collected included number of tweets, retweets, impressions, links, and user characteristics. Data were stratified by the presence of a COVID-19-related keyword, and a social media network analysis was further performed. Results: Of the 68,172 tweets, 10,093 contained COVID-19 content from 2809 users generating 65,513,669 impressions. More tweets with COVID-19 content contained links than without (P < 0.01). Network analysis demonstrated most users were physicians (48.10%), authoring the most tweets (40.38%), using the most mentions (32.15%), and retweeting the most (51.45%). The most impressions, however, were by healthcare organizations not providing clinical care (20,235,547 impressions, 30.89%). Users came from 80 countries, most from the United States (29.3%) and the United Kingdom (8.69%). During early March, COVID-19 dominated the #Radiology conversation, making up 54.67% of tweets the week of March 14 and 64.74% of impressions the week of March 21 compared to 13.97% of tweets and 16.76% of impressions in the remainder of the study period (P < 0.01).There was an influx of new users to the #Radiology conversation during this time period with more users tweeting about COVID-19 than not (P < 0.01). Conclusion: Discussion of COVID-19 in the #Radiology community increased significantly during the early weeks of the pandemic. Real time sharing and collaboration proved a useful tool when rapid information dissemination was needed to manage an emerging pathogen.

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APA

Lazaga, M. K. G., Dowell, J. D., & Makary, M. S. (2021). Characterization of the #Radiology Twitter Conversation During the Global COVID-19 Pandemic. Current Problems in Diagnostic Radiology, 50(3), 275–283. https://doi.org/10.1067/j.cpradiol.2021.02.006

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