Media Bias Matters: Understanding the Impact of Politically Biased News on Vaccine Attitudes in Social Media
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arXiv
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| Autores principales: | , , , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| _version_ | 1866913256607580160 |
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| author | Jiang, Bohan Cheng, Lu Tan, Zhen Guo, Ruocheng Liu, Huan |
| author_facet | Jiang, Bohan Cheng, Lu Tan, Zhen Guo, Ruocheng Liu, Huan |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_04009 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Media Bias Matters: Understanding the Impact of Politically Biased News on Vaccine Attitudes in Social Media Jiang, Bohan Cheng, Lu Tan, Zhen Guo, Ruocheng Liu, Huan Social and Information Networks Computation and Language Computers and Society Physics and Society 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. |
| title | Media Bias Matters: Understanding the Impact of Politically Biased News on Vaccine Attitudes in Social Media |
| topic | Social and Information Networks Computation and Language Computers and Society Physics and Society |
| url | https://arxiv.org/abs/2403.04009 |