Writing about COVID-19 vaccines: Emotional profiling unravels how mainstream and alternative press framed AstraZeneca, Pfizer and vaccination campaigns
arXiv:2201.07538 · doi:10.1038/s41598-022-18472-6
Abstract
Since their announcement in November 2020, COVID-19 vaccines were largely debated by the press and social media. With most studies focusing on COVID-19 disinformation in social media, little attention has been paid to how mainstream news outlets framed COVID-19 narratives compared to alternative sources. To fill this gap, we use cognitive network science and natural language processing to reconstruct time-evolving semantic and emotional frames of 5745 Italian news, that were massively re-shared on Facebook and Twitter, about COVID-19 vaccines. We found consistently high levels of trust/anticipation and less disgust in the way mainstream sources framed the general idea of "vaccine/vaccino". These emotions were crucially missing in the ways alternative sources framed COVID-19 vaccines. More differences were found within specific instances of vaccines. Alternative news included titles framing the AstraZeneca vaccine with strong levels of sadness, absent in mainstream titles. Mainstream news initially framed "Pfizer" along more negative associations with side effects than "AstraZeneca". With the temporary suspension of the latter, on March 15th 2021, we identified a semantic/emotional shift: Even mainstream article titles framed "AstraZeneca" as semantically richer in negative associations with side effects, while "Pfizer" underwent a positive shift in valence, mostly related to its higher efficacy. "Thrombosis" entered the frame of vaccines together with fearful conceptual associations, while "death" underwent an emotional shift, steering towards fear in alternative titles and losing its hopeful connotation in mainstream titles. Our findings expose crucial aspects of the emotional narratives around COVID-19 vaccines adopted by the press, highlighting the need to understand how alternative and mainstream media report vaccination news.
16 pages, 5 figures
References in corpus (11)
- Fast unfolding of communities in large networks
- Social Media Polarization and Echo Chambers in the Context of COVID-19: Case Study
- The Semantic Brand Score
- Text authorship identified using the dynamics of word co-occurrence networks
- Probing the topological properties of complex networks modeling short written texts
- PyPlutchik: visualising and comparing emotion-annotated corpora
- Structure-semantics interplay in complex networks and its effects on the predictability of similarity in texts
- The voice of few, the opinions of many: evidence of social biases in Twitter COVID-19 fake news sharing
- The Impact of Disinformation on a Controversial Debate on Social Media
- Forma mentis networks reconstruct how Italian high schoolers and international STEM experts perceive teachers, students, scientists, and school
- #Brexit: Leave or Remain? The Role of User's Community and Diachronic Evolution on Stance Detection