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Computer Science > Social and Information Networks

Title: Media Bias Matters: Understanding the Impact of Politically Biased News on Vaccine Attitudes in Social Media

Abstract: 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.
Comments: 9 pages, 6 figures, 3 tables
Subjects: Social and Information Networks (cs.SI); Computation and Language (cs.CL); Computers and Society (cs.CY); Physics and Society (physics.soc-ph)
Cite as: arXiv:2403.04009 [cs.SI]
  (or arXiv:2403.04009v1 [cs.SI] for this version)

Submission history

From: Bohan Jiang [view email]
[v1] Wed, 6 Mar 2024 19:41:02 GMT (717kb,D)

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