Please use this identifier to cite or link to this item:
Title: How do sentiments affect virality on Twitter?
Authors: Jiménez-Zafra, Salud M.
Sáez-Castillo, Antonio J.
Conde-Sánchez, Antonio
Martín-Valdivia, M. Teresa
Abstract: 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.
Keywords: Virality
Sentiment Analysis
Generalized Waring Regression
Issue Date: 14-Apr-2021
metadata.dc.description.sponsorship: This work has been partially supported by a grant from Fondo Social Europeo, Administration of the Junta de Andalucía (DOC_01073), Ministerio de Educación Cultura y Deporte (MECD – scholarship FPU014/00983), Fondo Europeo de Desarrollo Regional (FEDER) and LIVING-LANG project (RTI2018-094653-B-C21) from the Spanish Government.
Publisher: The Royal Society
Appears in Collections:DEIO-Artículos

Files in This Item:
File Description SizeFormat 
rsos.201756.pdfVersión publicada414,39 kBAdobe PDFView/Open

This item is protected by original copyright

Items in RUJA are protected by copyright, with all rights reserved, unless otherwise indicated.