Trend analysis of COVID-19 mis/disinformation narratives-A 3-year study.

Autor: Bonka Kotseva, Irene Vianini, Nikolaos Nikolaidis, Nicolò Faggiani, Kristina Potapova, Caroline Gasparro, Yaniv Steiner, Jessica Scornavacche, Guillaume Jacquet, Vlad Dragu, Leonida Della Rocca, Stefano Bucci, Aldo Podavini, Marco Verile, Charles Macmillan, Jens P Linge
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: PLoS ONE, Vol 18, Iss 11, p e0291423 (2023)
Druh dokumentu: article
ISSN: 1932-6203
DOI: 10.1371/journal.pone.0291423
Popis: To tackle the COVID-19 infodemic, we analysed 58,625 articles from 460 unverified sources, that is, sources that were indicated by fact checkers and other mis/disinformation experts as frequently spreading mis/disinformation, covering the period from 1 January 2020 to 31 December 2022. Our aim was to identify the main narratives of COVID-19 mis/disinformation, develop a codebook, automate the process of narrative classification by training an automatic classifier, and analyse the spread of narratives over time and across countries. Articles were retrieved with a customised version of the Europe Media Monitor (EMM) processing chain providing a stream of text items. Machine translation was employed to automatically translate non-English text to English and clustering was carried out to group similar articles. A multi-level codebook of COVID-19 mis/disinformation narratives was developed following an inductive approach; a transformer-based model was developed to classify all text items according to the codebook. Using the transformer-based model, we identified 12 supernarratives that evolved over the three years studied. The analysis shows that there are often real events behind mis/disinformation trends, which unverified sources misrepresent or take out of context. We established a process that allows for near real-time monitoring of COVID-19 mis/disinformation. This experience will be useful to analyse mis/disinformation about other topics, such as climate change, migration, and geopolitical developments.
Databáze: Directory of Open Access Journals
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