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Social media and public perception as core aspect of public health: the cautionary case of @realdonaldtrump and COVID-19


Peterson, Jeffrey; Fuentes, Agustin (2021), Social media and public perception as core aspect of public health: the cautionary case of @realdonaldtrump and COVID-19, Dryad, Dataset,


The social media milieu in which we are enmeshed has substantive impacts on our beliefs and perceptions. Recent work has established that this can play a role in influencing understanding of, and reactions to, public health information. Twitter, in particular, appears to play a substantive role in the public health information ecosystem. From July 25th, 2020 to November 15th, 2020, we collected weekly tweets related to COVID-19 keywords and assessed their networks, patterns and properties. Our analyses revealed the dominance of a handful of individual accounts as central structuring agents in the networks of tens of thousands of tweets and retweets, and thus millions of views, related to specific COVID-19 keywords. These few individual accounts and the content of their tweets, mentions, and retweets are substantially overrepresented in terms of public exposure to, and thus interaction with, critical elements of public health information in the pandemic. Here we report on one particularly striking aspect of our dataset: the prominent position of @realdonaldtrump in Twitter networks related to four key terms of the COVID-19 pandemic in 2020.


Data were collected weekly from July 25th, 2020 to November 15th, 2020 using NodeXL Pro. We instructed NodeXL Pro to collect tweets for each keyword: 1) Coronavirus origin; 2) Coronavirus vaccine; 3) COVID-19; 4) Fauci; 5) Mask; 6) Open (school OR economy); and 7) Social distancing. Data from keywords 4-7 are presented in this dataset and analyzed in the corresponding paper. Data are provided in the format in which they are compiled via NodeXL Pro.


John Templeton Foundation