Evidence map›Paper›PMID 35731785›Full record

ArticlePloS one2022

Analyzing COVID-19 disinformation on Twitter using the hashtags #scamdemic and #plandemic: Retrospective study.

Heather D Lanier, Marlon I Diaz, Sameh N Saleh, Christoph U Lehmann, Richard J Medford

Abstract read
In one paragraph

Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

25 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. When Infodemic Meets Epidemic: Systematic Literature Review.JMIR public health and surveillance · 2025
    Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. A National Discussion of COVID-19 on Twitter.Journal of the Association of Medical Microbiology and Infectious Disease Canada = Journal officiel de l'Association pour la microbiologie medicale et l'infectiologie Canada · 2024
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Public Health Policy, Political Ideology, and Public Emotion Related to COVID-19 in the U.S.International journal of environmental research and public health · 2023
    Article
  16. Review
  17. Article
  18. Article
  19. Rejoinder 2: Educating kids during a pandemic: More "farmers," fewer experts.Journal of the Canadian Academy of Child and Adolescent Psychiatry = Journal de l'Academie canadienne de psychiatrie de l'enfant et de l'adolescent · 2023
    Article
  20. Analyzing an Emerging Pandemic on Twitter: Monkeypox.Open forum infectious diseases · 2023
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Heather D LanierClinical Informatics Center, UT Southwestern Medical Center, Dallas, Texas, United States of America.ORCID 0000-0003-2962-5955
Marlon I DiazClinical Informatics Center, UT Southwestern Medical Center, Dallas, Texas, United States of America.
Sameh N SalehClinical Informatics Center, UT Southwestern Medical Center, Dallas, Texas, United States of America.
Christoph U LehmannClinical Informatics Center, UT Southwestern Medical Center, Dallas, Texas, United States of America.ORCID 0000-0001-9559-4646
Richard J MedfordClinical Informatics Center, UT Southwestern Medical Center, Dallas, Texas, United States of America.ORCID 0000-0001-9814-8043

Funding

UT Southwestern Center for Translational MedicineUL1TR003163 · NCATS · UT SOUTHWESTERN MEDICAL CENTER · PI TOTO, ROBERT DANIEL · 2021 to 2025
$39.3M
NCATS NIH HHS UL1 TR003163
6 · The paper itself

Abstract

introductionThe use of social media during the COVID-19 pandemic has led to an "infodemic" of mis- and disinformation with potentially grave consequences. To explore means of counteracting disinformation, we analyzed tweets containing the hashtags #Scamdemic and #Plandemic.

methodsUsing a Twitter scraping tool called twint, we collected 419,269 English-language tweets that contained "#Scamdemic" or "#Plandemic" posted in 2020. Using the Twitter application-programming interface, we extracted the same tweets (by tweet ID) with additional user metadata. We explored descriptive statistics of tweets including their content and user profiles, analyzed sentiments and emotions, performed topic modeling, and determined tweet availability in both datasets.

resultsAfter removal of retweets, replies, non-English tweets, or duplicate tweets, 40,081 users tweeted 227,067 times using our selected hashtags. The mean weekly sentiment was overall negative for both hashtags. One in five users who used these hashtags were suspended by Twitter by January 2021. Suspended accounts had an average of 610 followers and an average of 6.7 tweets per user, while active users had an average of 472 followers and an average of 5.4 tweets per user. The most frequent tweet topic was "Complaints against mandates introduced during the pandemic" (79,670 tweets), which included complaints against masks, social distancing, and closures. DISCUSSION: While social media has democratized speech, it also permits users to disseminate potentially unverified or misleading information that endangers people's lives and public health interventions. Characterizing tweets and users that use hashtags associated with COVID-19 pandemic denial allowed us to understand the extent of misinformation. With the preponderance of inaccessible original tweets, we concluded that posters were in denial of the COVID-19 pandemic and sought to disperse related mis- or disinformation resulting in suspension.

conclusionLeveraging 227,067 tweets with the hashtags #scamdemic and #plandemic in 2020, we were able to elucidate important trends in public disinformation about the COVID-19 vaccine.

Indexed as

COVID-19Social MediaCOVID-19 VaccinesDisinformationHumansPandemicsRetrospective StudiesCOVID-19 Vaccines

Identifiers

PMID35731785
PMCPMC9216575

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.