Impacto de las emociones vertidas por diarios digitales en Twitter
Autor:
Arce García, Sergio
; Orviz Martínez, Natalia
; Cuervo Carabel, Tatiana
Fecha:
09/2020Palabra clave:
prensa digital; diarios; periodismo digital; machine learning; redes sociales; medios sociales; Twitter; emociones; sentimientos; polaridad; pluralismo informativo; discursos; reacciones; opinión pública; digital media; newspapers; digital journalism; social networks; social media; emotions; feelings; polarity; media pluralism; speech; reactions; public opinion; JCR; Scopus
Revista / editorial:
Profesional de la InformaciónTipo de Ítem:
Articulo Revista IndexadaResumen:
The use of Twitter by newspapers is widespread and is a way to keep readers informed in real time. In this article, we analyze the discourse of the messages released by the ten main general information newspapers in Spain and the reactions they provoked on the social network. The objective is to analyze whether the emotional discourse of the news in each newspaper caused greater dissemination among and attention from users, as well as to determine the emotions and feelings expressed by them. To do so, news about important events such as court judgements, street riots, and general elections was followed between October and November 2019. A total of 124,897 tweets collected using machine-learning techniques were analyzed by the application of algorithms which allowed the determination of emotions and valences of feelings. We carried out statistical studies and produced graphs showing the dependence between emotional variables and positive or negative sentimental valence. The results showed that, in general, newspapers do not use an excessive amount of emotional speech with the aim of impacting their public. However, differences were found among the newspapers in terms of trying to encourage reader loyalty. The reaction of the users was more linked to the informative facts themselves and the emotions they provoked than to the type of emotional and/or polarized discourse. The day-to-day information determines to a large extent what is consumed by Twitter users, in which changing modes of speech are observed depending on the editorial line of each newspaper.
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