mlsanityData to 7 Oct 2026

COVID-19 Vaccine Misinformation Campaigns and Social Media Narratives

arXiv 2106.08423 ↗First posted 15 Jun 2021cs.SI cs.CY cs.LGcited by 7

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Abstract (arXiv)

COVID-19 vaccine hesitancy has increased concerns about vaccine uptake required to overcome the pandemic and protect public health. A critical factor associated with anti-vaccine attitudes is the information shared on social media. In this work, we investigate misinformation communities and narratives that can contribute to COVID-19 vaccine hesitancy. During the pandemic, anti-science and political misinformation/conspiracies have been rampant on social media. Therefore, we investigate misinformation and conspiracy groups and their characteristic behaviours in Twitter data collected on COVID-19 vaccines. We identify if any suspicious coordinated efforts are present in promoting vaccine misinformation, and find two suspicious groups - one promoting a 'Great Reset' conspiracy which suggests that the pandemic is orchestrated by world leaders to take control of the economy, with vaccine related misinformation and strong anti-vaccine and anti-social messages such as no lock-downs; and another promoting the Bioweapon theory. Misinformation promoted is largely from the anti-vaccine and far-right communities in the 3-core of the retweet graph, with its tweets proportion of conspiracy and questionable sources to reliable sources being much higher. In comparison with the mainstream and health news, the right-leaning community is more influenced by the anti-vaccine and far-right communities, which is also reflected in the disparate vaccination rates in left and right U.S. states. The misinformation communities are also more vocal, either in vaccine or other discussions, relative to remaining communities, besides other behavioral differences.

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 12 of its 37 references that are in the map. First posted on arXiv 15 Jun 2021.

Builds on

12 of 37 references.

References · 12

  1. 2016Enriching Word Vectors with Subword Informationcited by 1,578
  2. 2020Uncovering Coordinated Networks on Social Media: Methods and Case Studiescited by 49
  3. 2020Identifying Coordinated Accounts on Social Media through Hidden Influence and Group Behaviourscited by 46
  4. 2020Detection of Novel Social Bots by Ensembles of Specialized Classifierscited by 32
  5. 2020Characterizing COVID-19 Misinformation Communities Using a Novel Twitter Datasetcited by 32
  6. 2015Quantifying Controversy in Social Mediacited by 28
  7. 2021COVID-19 Vaccine Hesitancy on Social Media: Building a Public Twitter Dataset of Anti-vaccine Content, Vaccine Misinformation and Conspiraciescited by 17
  8. 2020A first look at COVID-19 information and misinformation sharing on Twittercited by 13
  9. 2020Falling into the Echo Chamber: the Italian Vaccination Debate on Twittercited by 12
  10. 2018Characterizing the 2016 Russian IRA Influence Campaigncited by 11
  11. 2021Auditing E-Commerce Platforms for Algorithmically Curated Vaccine Misinformationcited by 11
  12. 2021Misinformation Warning Labels: Twitter's Soft Moderation Effects on COVID-19 Vaccine Belief Echoescited by 3

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Cited by year

Citing papers per year: 2022: 2; 2023: 3; 2024: 2.

7 papers.