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Identifying Vaccine Hesitant Communities on Twitter and their Geolocations: A Network Approach
|Title:||Identifying Vaccine Hesitant Communities on Twitter and their Geolocations: A Network Approach|
Featherstone , Jade D.
Barnett, George A.
|Keywords:||Socia Media and Healthcare Technology|
|Date Issued:||05 Jan 2021|
|Abstract:||Vaccine misinformation online may contribute to the increase of anti-vaccine sentiment and vaccine-hesitant behaviors. Social network data was used to identify Twitter vaccine influencers, their online twitter communities, and their geolocations to determine pro-vaccine and vaccine-hesitant online communities. We explored 139,433 tweets and identified 420 vaccine Twitter influencers—opinion leaders and assessed 13,487 of their tweets and 7,731 of their connections. Semantic network analysis was employed to determine twitter conversation themes. Results suggest that locating social media influencers is an efficient way to identify and target vaccine-hesitant communities online. We discuss the implications of using this process for public health education and disease management.|
|Rights:||Attribution-NonCommercial-NoDerivatives 4.0 International|
|Appears in Collections:||
Socia Media and Healthcare Technology|
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