The first months of 2020 saw the coronavirus pandemic explode. Moving from China, it arrived in Europe and hit Italy. The place where the debate around it exploded was the media ecosystem. In a short time, it was an explosion of tweets related to the hashtag #coronavirus on Twitter. With the aim of reconstructing the meanings of the hashtag and the content, in terms of sentiment and opinions, of the reactions of the Italians, we collected in a large size corpus, the hundred thousand Italian tweets containing the #coronavirus produced during the media hype period from the Twitter repository (February 24th - 28th, 2020). Media hype period was discovered by digging in the online articles of “la Repubblica”, based on the presence of the words: coronavirus and Italy. The media hype is February 26th. The corpus underwent Emotional Text Mining (ETM). ETM is an unsupervised methodology, which allows social profiling based on communication; it is a bottom-up semiotic approach used to classify unstructured data by means of a multivariate analysis (cluster analysis and correspondence analysis). The study of the word chosen to talk about a topic and their co-occurrence allows the understanding of people’s symbolizations, representations, and sentiment, about the coronavirus. In a retrospective logic, this mechanism allows us to reconstruct the sensemaking and nuances of meaning attributed by users to the coronavirus hashtag.

The flame of the Coronavirus in Italy. Looking for fear arousing appeal during the media hype period on Twitter / Boccia Artieri, G.; Greco, F.; La Rocca, G.. - In: REVUE INTERNATIONALE DE SOCIOLOGIE. - ISSN 0390-6701. - 31:2(2021), pp. 287-309. [10.1080/03906701.2021.1947950]

The flame of the Coronavirus in Italy. Looking for fear arousing appeal during the media hype period on Twitter

Greco F.;La Rocca G.
2021

Abstract

The first months of 2020 saw the coronavirus pandemic explode. Moving from China, it arrived in Europe and hit Italy. The place where the debate around it exploded was the media ecosystem. In a short time, it was an explosion of tweets related to the hashtag #coronavirus on Twitter. With the aim of reconstructing the meanings of the hashtag and the content, in terms of sentiment and opinions, of the reactions of the Italians, we collected in a large size corpus, the hundred thousand Italian tweets containing the #coronavirus produced during the media hype period from the Twitter repository (February 24th - 28th, 2020). Media hype period was discovered by digging in the online articles of “la Repubblica”, based on the presence of the words: coronavirus and Italy. The media hype is February 26th. The corpus underwent Emotional Text Mining (ETM). ETM is an unsupervised methodology, which allows social profiling based on communication; it is a bottom-up semiotic approach used to classify unstructured data by means of a multivariate analysis (cluster analysis and correspondence analysis). The study of the word chosen to talk about a topic and their co-occurrence allows the understanding of people’s symbolizations, representations, and sentiment, about the coronavirus. In a retrospective logic, this mechanism allows us to reconstruct the sensemaking and nuances of meaning attributed by users to the coronavirus hashtag.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1580815
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