Media Bias Matters: Understanding the Impact of Politically Biased News
  on Vaccine Attitudes in Social Media
Bohan Jiang Lu Cheng Zhen Tan Ruocheng Guo Huan Liu
News media has been utilized as a political tool to stray from facts,
presenting biased claims without evidence. Amid the COVID-19 pandemic,
politically biased news (PBN) has significantly undermined public trust in
vaccines, despite strong medical evidence supporting their efficacy. In this
paper, we analyze: (i) how inherent vaccine stances subtly influence
individuals' selection of news sources and participation in social media
discussions; and (ii) the impact of exposure to PBN on users' attitudes toward
vaccines. In doing so, we first curate a comprehensive dataset that connects
PBN with related social media discourse. Utilizing advanced deep learning and
causal inference techniques, we reveal distinct user behaviors between social
media groups with various vaccine stances. Moreover, we observe that
individuals with moderate stances, particularly the vaccine-hesitant majority,
are more vulnerable to the influence of PBN compared to those with extreme
views. Our findings provide critical insights to foster this line of research.