ACMdel Barrio, David AlonsoGatica-Perez, Daniel2024-02-202024-02-202024-02-202022-01-0110.1145/3512732.3533588https://infoscience.epfl.ch/handle/20.500.14299/204754WOS:001122483300007Understanding how high-quality newspapers present and discuss major news plays a role towards tackling disinformation, as it contributes to the characterization of the full ecosystem in which information circulates. In this paper, we present an analysis of how the European press treated the Covid-19 vaccination issue in 2020-2021. We first collected a dataset of over 50,000 online articles published by 19 newspapers from five European countries over 22 months. Then, we performed analyses on headlines and full articles with natural language processing tools, including named entity recognition, topic modeling, and sentiment analysis, to identify main actors, subtopics, and tone, and to compare trends across countries. The results show several consistencies across countries and subtopics (e.g. a prevalence of neutral tone and relatively more negative sentiment for non-neutral articles, with few exceptions like the case of vaccine brands), but also differences (e.g., distinctly high negative-to-positive ratios for the no-vax subtopic.) Overall, our work provides a point of comparison to other news sources on a topic where disinformation and misinformation have resulted in increased risks and negative outcomes for people's health.TechnologyCovid-19 VaccinationDisinformationEuropean NewsTopic ModelingSentiment Analysistext::conference output::conference proceedings::conference paper