Please use this identifier to cite or link to this item: http://hdl.handle.net/10125/71096

Identifying Vaccine Hesitant Communities on Twitter and their Geolocations: A Network Approach

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Title:Identifying Vaccine Hesitant Communities on Twitter and their Geolocations: A Network Approach
Authors:Ruiz, Jeanette
Featherstone , Jade D.
Barnett, George A.
Keywords:Socia Media and Healthcare Technology
social networks
twitter
vaccine hesitancy
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.
Pages/Duration:6 pages
URI:http://hdl.handle.net/10125/71096
ISBN:978-0-9981331-4-0
DOI:10.24251/HICSS.2021.480
Rights:Attribution-NonCommercial-NoDerivatives 4.0 International
https://creativecommons.org/licenses/by-nc-nd/4.0/
Appears in Collections: Socia Media and Healthcare Technology


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