del Barrio, David AlonsoGatica-Perez, Daniel2023-10-092023-10-092023-10-092023-01-0110.1145/3592572.3592845https://infoscience.epfl.ch/handle/20.500.14299/201435WOS:001059176200008This 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.Computer Science, Artificial IntelligenceComputer Science, Interdisciplinary ApplicationsComputer Scienceno-vaxdisinformationnlptopic modelingword embeddingsentiment analysisnamed entity recognitionsemantic networktext::conference output::conference proceedings::conference paper