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Winning! Election returns and engagement in social media

This article analyzes social media engagement when elections are adjudicated to one of the contending parties. We extend existing models of political dialogue to explain differences in social media engagement (i.e. time-to-retweet) when users support the winner or losers of an election. We show that...

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Detalles Bibliográficos
Autores principales: Calvo, Ernesto, Ventura, Tiago, Aruguete, Natalia, Waisbord, Silvio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9977005/
https://www.ncbi.nlm.nih.gov/pubmed/36857337
http://dx.doi.org/10.1371/journal.pone.0281475
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author Calvo, Ernesto
Ventura, Tiago
Aruguete, Natalia
Waisbord, Silvio
author_facet Calvo, Ernesto
Ventura, Tiago
Aruguete, Natalia
Waisbord, Silvio
author_sort Calvo, Ernesto
collection PubMed
description This article analyzes social media engagement when elections are adjudicated to one of the contending parties. We extend existing models of political dialogue to explain differences in social media engagement (i.e. time-to-retweet) when users support the winner or losers of an election. We show that users who support the winning candidate are more engaged and have a lower time-to-retweet. We also show heterogeneity in Twitter engagement conditional on the number of followers, with accounts with more followers being less sensitive to the election result. We measure the effect of electoral adjudication using a regression discontinuity design, with estimates by winning or losing status, and for accounts with many followers (high authority) or with few followers (low authority). Analyses use Twitter data collected in Argentina (2019), Brazil (2018), the United Kingdom (2019), and the United States (2016).
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spelling pubmed-99770052023-03-02 Winning! Election returns and engagement in social media Calvo, Ernesto Ventura, Tiago Aruguete, Natalia Waisbord, Silvio PLoS One Research Article This article analyzes social media engagement when elections are adjudicated to one of the contending parties. We extend existing models of political dialogue to explain differences in social media engagement (i.e. time-to-retweet) when users support the winner or losers of an election. We show that users who support the winning candidate are more engaged and have a lower time-to-retweet. We also show heterogeneity in Twitter engagement conditional on the number of followers, with accounts with more followers being less sensitive to the election result. We measure the effect of electoral adjudication using a regression discontinuity design, with estimates by winning or losing status, and for accounts with many followers (high authority) or with few followers (low authority). Analyses use Twitter data collected in Argentina (2019), Brazil (2018), the United Kingdom (2019), and the United States (2016). Public Library of Science 2023-03-01 /pmc/articles/PMC9977005/ /pubmed/36857337 http://dx.doi.org/10.1371/journal.pone.0281475 Text en © 2023 Calvo et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Calvo, Ernesto
Ventura, Tiago
Aruguete, Natalia
Waisbord, Silvio
Winning! Election returns and engagement in social media
title Winning! Election returns and engagement in social media
title_full Winning! Election returns and engagement in social media
title_fullStr Winning! Election returns and engagement in social media
title_full_unstemmed Winning! Election returns and engagement in social media
title_short Winning! Election returns and engagement in social media
title_sort winning! election returns and engagement in social media
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9977005/
https://www.ncbi.nlm.nih.gov/pubmed/36857337
http://dx.doi.org/10.1371/journal.pone.0281475
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