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How do sentiments affect virality on Twitter?
Virality on Twitter is catching the attention of researchers, trying to identify factors which increase or decrease the probability of retweeting. We study how terms expressing sentiments affect retweeting frequencies by means of a regression model on the number of retweets, which is specially accur...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8059576/ https://www.ncbi.nlm.nih.gov/pubmed/33996120 http://dx.doi.org/10.1098/rsos.201756 |
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author | Jiménez-Zafra, Salud María Sáez-Castillo, Antonio José Conde-Sánchez, Antonio Martín-Valdivia, María Teresa |
author_facet | Jiménez-Zafra, Salud María Sáez-Castillo, Antonio José Conde-Sánchez, Antonio Martín-Valdivia, María Teresa |
author_sort | Jiménez-Zafra, Salud María |
collection | PubMed |
description | Virality on Twitter is catching the attention of researchers, trying to identify factors which increase or decrease the probability of retweeting. We study how terms expressing sentiments affect retweeting frequencies by means of a regression model on the number of retweets, which is specially accurate to deal with virality. We focus on the Spanish political situation during the pseudo-referendum held in Catalonia on 1 October 2017. We have found that the use of negativity in a tweet increases the probability of retweeting and that iSOL lexicon is the one that better determines the relationship between polarity and virality. |
format | Online Article Text |
id | pubmed-8059576 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | The Royal Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-80595762021-05-14 How do sentiments affect virality on Twitter? Jiménez-Zafra, Salud María Sáez-Castillo, Antonio José Conde-Sánchez, Antonio Martín-Valdivia, María Teresa R Soc Open Sci Computer Science and Artificial Intelligence Virality on Twitter is catching the attention of researchers, trying to identify factors which increase or decrease the probability of retweeting. We study how terms expressing sentiments affect retweeting frequencies by means of a regression model on the number of retweets, which is specially accurate to deal with virality. We focus on the Spanish political situation during the pseudo-referendum held in Catalonia on 1 October 2017. We have found that the use of negativity in a tweet increases the probability of retweeting and that iSOL lexicon is the one that better determines the relationship between polarity and virality. The Royal Society 2021-04-14 /pmc/articles/PMC8059576/ /pubmed/33996120 http://dx.doi.org/10.1098/rsos.201756 Text en © 2021 The Authors. https://creativecommons.org/licenses/by/4.0/Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, provided the original author and source are credited. |
spellingShingle | Computer Science and Artificial Intelligence Jiménez-Zafra, Salud María Sáez-Castillo, Antonio José Conde-Sánchez, Antonio Martín-Valdivia, María Teresa How do sentiments affect virality on Twitter? |
title | How do sentiments affect virality on Twitter? |
title_full | How do sentiments affect virality on Twitter? |
title_fullStr | How do sentiments affect virality on Twitter? |
title_full_unstemmed | How do sentiments affect virality on Twitter? |
title_short | How do sentiments affect virality on Twitter? |
title_sort | how do sentiments affect virality on twitter? |
topic | Computer Science and Artificial Intelligence |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8059576/ https://www.ncbi.nlm.nih.gov/pubmed/33996120 http://dx.doi.org/10.1098/rsos.201756 |
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