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Greed communication predicts the approval and reach of US senators’ tweets

Social media are at the forefront of modern political campaigning. They allow politicians to communicate directly with constituents and constituents to endorse politicians’ messages and share them with their networks. Analyzing every tweet of all US senators holding office from 2013 to 2021 (861,104...

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Detalles Bibliográficos
Autores principales: Mercadante, Eric J., Tracy, Jessica L., Götz, Friedrich M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10089212/
https://www.ncbi.nlm.nih.gov/pubmed/36877836
http://dx.doi.org/10.1073/pnas.2218680120
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author Mercadante, Eric J.
Tracy, Jessica L.
Götz, Friedrich M.
author_facet Mercadante, Eric J.
Tracy, Jessica L.
Götz, Friedrich M.
author_sort Mercadante, Eric J.
collection PubMed
description Social media are at the forefront of modern political campaigning. They allow politicians to communicate directly with constituents and constituents to endorse politicians’ messages and share them with their networks. Analyzing every tweet of all US senators holding office from 2013 to 2021 (861,104 tweets from 140 senators), we identify a psycholinguistic factor, greed communication, that robustly predicts increased approval (favorites) and reach (retweets). These effects persist when tested against diverse established psycholinguistic predictors of political content dissemination on social media and various other psycholinguistic variables. We further find that greed communication in the tweets of Democratic senators is associated with greater approval and retweeting compared to greed communication in the tweets of Republican senators, especially when those tweets also mention political outgroups.
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spelling pubmed-100892122023-04-12 Greed communication predicts the approval and reach of US senators’ tweets Mercadante, Eric J. Tracy, Jessica L. Götz, Friedrich M. Proc Natl Acad Sci U S A Social Sciences Social media are at the forefront of modern political campaigning. They allow politicians to communicate directly with constituents and constituents to endorse politicians’ messages and share them with their networks. Analyzing every tweet of all US senators holding office from 2013 to 2021 (861,104 tweets from 140 senators), we identify a psycholinguistic factor, greed communication, that robustly predicts increased approval (favorites) and reach (retweets). These effects persist when tested against diverse established psycholinguistic predictors of political content dissemination on social media and various other psycholinguistic variables. We further find that greed communication in the tweets of Democratic senators is associated with greater approval and retweeting compared to greed communication in the tweets of Republican senators, especially when those tweets also mention political outgroups. National Academy of Sciences 2023-03-06 2023-03-14 /pmc/articles/PMC10089212/ /pubmed/36877836 http://dx.doi.org/10.1073/pnas.2218680120 Text en Copyright © 2023 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by/4.0/This open access article is distributed under Creative Commons Attribution License 4.0 (CC BY) (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Social Sciences
Mercadante, Eric J.
Tracy, Jessica L.
Götz, Friedrich M.
Greed communication predicts the approval and reach of US senators’ tweets
title Greed communication predicts the approval and reach of US senators’ tweets
title_full Greed communication predicts the approval and reach of US senators’ tweets
title_fullStr Greed communication predicts the approval and reach of US senators’ tweets
title_full_unstemmed Greed communication predicts the approval and reach of US senators’ tweets
title_short Greed communication predicts the approval and reach of US senators’ tweets
title_sort greed communication predicts the approval and reach of us senators’ tweets
topic Social Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10089212/
https://www.ncbi.nlm.nih.gov/pubmed/36877836
http://dx.doi.org/10.1073/pnas.2218680120
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