Tracing the dynamics of misinformation and vaccine stance in Finland amid COVID-19

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A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
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Date

2024-03-27

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Department of Computer Science

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Language

en

Pages

25

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INFORMATION COMMUNICATION AND SOCIETY

Abstract

This study analyzed 1,683,700 vaccine-related tweets in Finnish using FinBERT language model, Botometer, and BERTopic, from December 2019 to October 2022. A strong correlation was identified between Negative Stance towards Vaccines (NSV) and misinformation, with an upward trend over time and a significant role of malicious bot accounts. Topic modeling revealed persistent themes of vaccine skepticism and diverse misinformation themes adapting to debunking efforts. Approximately a third of tweets contained misinformation, irrespective of source reliability, leading to increased NSV. The study observed a gap in active countering of misinformation by authorities, suggesting proactive involvement by public authorities, public education for effective misinformation management and social media literacy.

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Keywords

COVID-19, Finland, Misinformation, Social media, Text classification, Vaccine stance

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DOI

10.1080/1369118X.2024.2331756

Citation

Unlu, A, Truong, S, Sawhney, N, Tammi, T & Sivelä, J 2024, ' Tracing the dynamics of misinformation and vaccine stance in Finland amid COVID-19 ', INFORMATION COMMUNICATION AND SOCIETY . https://doi.org/10.1080/1369118X.2024.2331756

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https://urn.fi/URN:NBN:fi:aalto-202404173161

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[article-cris] Perustieteiden korkeakoulu / SCI