# Writing about COVID-19 vaccines: Emotional profiling unravels how mainstream and alternative press framed AstraZeneca, Pfizer and vaccination campaigns arXiv: https://arxiv.org/abs/2201.07538 ยท HTML: https://mlsanity.com/paper/2201.07538/ ## Key facts - Cited by 3 papers in the map (data through 14 Oct 2026). - Builds on 26 of its 86 references that are in the map. - First posted on arXiv 19 Jan 2022. ## Builds on (most cited first, 26 of 26) - [Deep Biaffine Attention for Neural Dependency Parsing](https://mlsanity.com/paper/1611.01734/) (2016) - [Crowdsourcing a Word-Emotion Association Lexicon](https://mlsanity.com/paper/1308.6297/) (2013) - [The COVID-19 Social Media Infodemic](https://mlsanity.com/paper/2003.05004/) (2020) - [MITRE at SemEval-2016 Task 6: Transfer Learning for Stance Detection](https://mlsanity.com/paper/1606.03784/) (2016) - [Bots increase exposure to negative and inflammatory content in online social systems](https://mlsanity.com/paper/1802.07292/) (2018) - [Sentiment Analysis: Automatically Detecting Valence, Emotions, and Other Affectual States from Text](https://mlsanity.com/paper/2005.11882/) (2020) - [Social Media Polarization and Echo Chambers in the Context of COVID-19: Case Study](https://mlsanity.com/paper/2103.10979/) (2021) - [The Semantic Brand Score](https://mlsanity.com/paper/2105.05781/) (2021) - [Emotional Dynamics in the Age of Misinformation](https://mlsanity.com/paper/1505.08001/) (2015) - [The COVID-19 Infodemic: Twitter versus Facebook](https://mlsanity.com/paper/2012.09353/) (2020) - [Quantifying the Effect of Sentiment on Information Diffusion in Social Media](https://mlsanity.com/paper/1506.06072/) (2015) - [Revealing semantic and emotional structure of suicide notes with cognitive network science](https://mlsanity.com/paper/2007.12053/) (2020) - [Analysing Twitter Semantic Networks: the case of 2018 Italian Elections](https://mlsanity.com/paper/2009.02960/) (2020) - [PyPlutchik: visualising and comparing emotion-annotated corpora](https://mlsanity.com/paper/2105.04295/) (2021) - [Probing the topological properties of complex networks modeling short written texts](https://mlsanity.com/paper/1412.8504/) (2014) - [#Brexit: Leave or Remain? The Role of User's Community and Diachronic Evolution on Stance Detection](https://mlsanity.com/paper/2007.14936/) (2020) - [Cognitive network science for understanding online social cognitions: A brief review](https://mlsanity.com/paper/2102.12799/) (2021) - [Investigating Italian disinformation spreading on Twitter in the context of 2019 European elections](https://mlsanity.com/paper/1907.08170/) (2019) - [Structure-semantics interplay in complex networks and its effects on the predictability of similarity in texts](https://mlsanity.com/paper/1303.0350/) (2013) - [Text authorship identified using the dynamics of word co-occurrence networks](https://mlsanity.com/paper/1608.01965/) (2016) - [Paragraph-based complex networks: application to document classification and authenticity verification](https://mlsanity.com/paper/1806.08467/) (2018) - [Flow of online misinformation during the peak of the COVID-19 pandemic in Italy](https://mlsanity.com/paper/2010.01913/) (2020) - [Cognitive networks identify the content of English and Italian popular posts about COVID-19 vaccines: Anticipation, logistics, conspiracy and loss of trust](https://mlsanity.com/paper/2103.15909/) (2021) - [The Impact of Disinformation on a Controversial Debate on Social Media](https://mlsanity.com/paper/2106.15968/) (2021) - [Lack of evidence for correlation between COVID-19 infodemic and vaccine acceptance](https://mlsanity.com/paper/2107.07946/) (2021) - [The voice of few, the opinions of many: evidence of social biases in Twitter COVID-19 fake news sharing](https://mlsanity.com/paper/2112.01304/) (2021) ## Built on by (most cited first, 3 of 3) - [Developing a Natural Language Understanding Model to Characterize Cable News Bias](https://mlsanity.com/paper/2310.09166/) (2023) - [Cognitive modelling with multilayer networks: Insights, advancements and future challenges](https://mlsanity.com/paper/2210.00500/) (2022) - [Examining European Press Coverage of the Covid-19 No-Vax Movement: An NLP Framework](https://mlsanity.com/paper/2305.00182/) (2023) ## Abstract (arXiv) 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.