Setting the misinformation agenda
Modeling Covid-19 narratives in Twitter communities
Bibliographic Data
| ID | 6443610 |
|---|---|
| Authors | Ali Unlu (0000-0003-0140-7761, Finnish Institute for Health and Welfare (THL), Finland; Aalto University, Finland, corresponding author), Sophie Truong, Nitin Sawhney (0000-0002-8088-914X, Aalto University), Tuukka Tammi (0000-0001-5114-3026, Finnish Institute for Health and Welfare) |
| Year | 2024 |
| Volume | 27 |
| Issue | 7 |
| Pages | 3973-3997 |
| Publication date | 2024-02-23 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | New Media & Society (JOURNAL) |
| Journal identifiers | ISSN: 1461-4448 • E-ISSN: 1461-7315 |
| Publisher | SAGE Publishing (PUBLISHER • US) |
| DOI | 10.1177/14614448241232079 |
| OpenAlex | W4392102768 |
| Language | EN |
| Citations received | 3 |
| References cited | 55 |
This research investigates the dynamics of COVID-19 misinformation spread on Twitter within the unique context of Finland. Employing cutting-edge methodologies including text classification, topic modeling, social network analysis, and correspondence analysis (CA), the study analyzes 1.6 million Finnish tweets from December 2019 to October 2022. Misinformation tweets are identified through text classification and grouped into topics using BERTopic modeling. Applying the Leiden algorithm, the analysis uncovers retweet and mention networks, delineating distinct communities within each. CA determines these communities’ topical focuses, revealing how various groups prioritized different misinformation narratives throughout the pandemic. The findings demonstrate that influential, diverse communities introduce new misinformation, which then spreads to niche groups. This agenda-setting effect is amplified by social media algorithms optimized for engagement. The results provide valuable insights into how online communities shape public discourse during crises through the strategic dissemination of misinformation
2019-20 coronavirus outbreak · Art · Coronavirus disease 2019 (COVID-19 · Internet privacy · Literature · Media studies · Misinformation · Narrative · Political science · Public relations · Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 · Social media · Sociology · World Wide Web · Computer Science · Hate Speech and Cyberbullying Detection · Medicine · Misinformation and Its Impacts · Psychology · Social Media and Politics · Virology
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Demystifying the Covid-19 Infodemic
Hunting Conspiracy Theories During the Covid-19 Pandemic
| Citations per year | 1.5 |
|---|---|
| Citation span | 2024 - 2025 (2) |
| Highly cited | No |