Examining European Press Coverage of the Covid-19 No-Vax Movement: An NLP Framework
This study addresses the role of traditional media in combating disinformation for public health and media researchers, but it is incremental as it applies existing NLP methods to a new dataset.
The paper analyzed how European newspapers covered the Covid-19 anti-vaccine movement using NLP on 1,786 articles, finding that the press actively opposed hoaxes and criticized the trend regardless of political orientation.
This paper examines how the European press dealt with the no-vax reactions against the Covid-19 vaccine and the dis- and misinformation associated with this movement. Using a curated dataset of 1786 articles from 19 European newspapers on the anti-vaccine movement over a period of 22 months in 2020-2021, we used Natural Language Processing techniques including topic modeling, sentiment analysis, semantic relationship with word embeddings, political analysis, named entity recognition, and semantic networks, to understand the specific role of the European traditional press in the disinformation ecosystem. The results of this multi-angle analysis demonstrate that the European well-established press actively opposed a variety of hoaxes mainly spread on social media, and was critical of the anti-vax trend, regardless of the political orientation of the newspaper. This confirms the relevance of studying the role of high-quality press in the disinformation ecosystem.