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A comparative framework to analyze convergence on Twitter electoral conversations

Literature on social networks and elections has focused on predicting electoral outcomes rather than on understanding how the discussions between users evolve over time. As a result, most studies focus on a single election and few comparative studies exist. In this article, a framework to analyze Tw...

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Autores principales: Cárdenas-Sánchez, Daniel, Sampayo, Andrés Miguel, Rodríguez-Prieto, Maykol, Feged-Rivadeneira, Alejandro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9646886/
https://www.ncbi.nlm.nih.gov/pubmed/36352010
http://dx.doi.org/10.1038/s41598-022-21861-6
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author Cárdenas-Sánchez, Daniel
Sampayo, Andrés Miguel
Rodríguez-Prieto, Maykol
Feged-Rivadeneira, Alejandro
author_facet Cárdenas-Sánchez, Daniel
Sampayo, Andrés Miguel
Rodríguez-Prieto, Maykol
Feged-Rivadeneira, Alejandro
author_sort Cárdenas-Sánchez, Daniel
collection PubMed
description Literature on social networks and elections has focused on predicting electoral outcomes rather than on understanding how the discussions between users evolve over time. As a result, most studies focus on a single election and few comparative studies exist. In this article, a framework to analyze Twitter conversations about the election candidates is proposed. Using DeGroot’s consensus model (an assumption that all users are attempting to persuade others to talk about a candidate), this framework is useful to identify the structure and strength of connections of the mention networks on the months before an election day. It also helps to make comparisons between elections and identify patterns in different contexts. In concrete, it was found that elections in which the incumbent was running have slower convergence (more closed communities with fewer links between them) and that there is no difference between parliamentary and presidential elections. Therefore, there is evidence that the political system and the role of the incumbent in the election influences the way conversations on Twitter occur.
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spelling pubmed-96468862022-11-15 A comparative framework to analyze convergence on Twitter electoral conversations Cárdenas-Sánchez, Daniel Sampayo, Andrés Miguel Rodríguez-Prieto, Maykol Feged-Rivadeneira, Alejandro Sci Rep Article Literature on social networks and elections has focused on predicting electoral outcomes rather than on understanding how the discussions between users evolve over time. As a result, most studies focus on a single election and few comparative studies exist. In this article, a framework to analyze Twitter conversations about the election candidates is proposed. Using DeGroot’s consensus model (an assumption that all users are attempting to persuade others to talk about a candidate), this framework is useful to identify the structure and strength of connections of the mention networks on the months before an election day. It also helps to make comparisons between elections and identify patterns in different contexts. In concrete, it was found that elections in which the incumbent was running have slower convergence (more closed communities with fewer links between them) and that there is no difference between parliamentary and presidential elections. Therefore, there is evidence that the political system and the role of the incumbent in the election influences the way conversations on Twitter occur. Nature Publishing Group UK 2022-11-09 /pmc/articles/PMC9646886/ /pubmed/36352010 http://dx.doi.org/10.1038/s41598-022-21861-6 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Cárdenas-Sánchez, Daniel
Sampayo, Andrés Miguel
Rodríguez-Prieto, Maykol
Feged-Rivadeneira, Alejandro
A comparative framework to analyze convergence on Twitter electoral conversations
title A comparative framework to analyze convergence on Twitter electoral conversations
title_full A comparative framework to analyze convergence on Twitter electoral conversations
title_fullStr A comparative framework to analyze convergence on Twitter electoral conversations
title_full_unstemmed A comparative framework to analyze convergence on Twitter electoral conversations
title_short A comparative framework to analyze convergence on Twitter electoral conversations
title_sort comparative framework to analyze convergence on twitter electoral conversations
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9646886/
https://www.ncbi.nlm.nih.gov/pubmed/36352010
http://dx.doi.org/10.1038/s41598-022-21861-6
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