Supernarrative country distribution.

The table shows the country distribution of all supernarratives and narratives. The bigger the square, the more articles from the monitored sources of a given country have been assigned to the narrative in question. The colour represents the distribution of articles in percentile across the narrative. Using percentile allows us to display each source country’s ranking within each narrative, despite the different numbers of monitored sources for each country.</p

Evaluation results.

Results of the Precision, Recall and F1 evaluation of BERT classifier on test set.</p

Query. Keyword-based query.

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.</div

Evolution of anti-vax narratives.

The timeline shows the spread over time of “anti-vax narratives,” “anti-mandatory vaccination narratives,” and “anti-vax conspiracy theories”. (TIF)</p