How do sentiments affect virality on Twitter?
Author(s) -
Salud María Jiménez-Zafra,
Antonio José Sáez-Castillo,
Antonio Conde Sánchez,
María Teresa Martín Valdivia
Publication year - 2021
Publication title -
royal society open science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.84
H-Index - 51
ISSN - 2054-5703
DOI - 10.1098/rsos.201756
Subject(s) - affect (linguistics) , lexicon , focus (optics) , referendum , polarity (international relations) , computer science , psychology , artificial intelligence , politics , political science , communication , biology , law , cell , physics , genetics , optics
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.
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