Evidence map›Paper›PMID 30020821›Full record

ArticleCyberpsychology, behavior and social networking2018

Propagating and Debunking Conspiracy Theories on Twitter During the 2015-2016 Zika Virus Outbreak.

Michael J Wood

Abstract read
In one paragraph

Article in Cyberpsychology, behavior and social networking, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing 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

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

  1. Pooled it
  2. Trial
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Combating Misinformation by Sharing the Truth: a Study on the Spread of Fact-Checks on Social Media.Information systems frontiers : a journal of research and innovation · 2022
    Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

1 author.

Michael J WoodDepartment of Psychology, University of Winchester , Winchester, United Kingdom .

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The present study investigates the characteristics of discussion of conspiracy theories about the Zika virus outbreak of 2015-16 on Twitter. Content and social network analysis of a dataset of 25,162 original Tweets about Zika virus conspiracy theories showed that relative to debunking messages, conspiracy theories spread through a more decentralized network, are more likely to invoke supposedly knowledgeable authorities in making arguments, and ask more rhetorical questions. These trends can be understood in the context of previous work on conspiracy theories, including the "just asking questions" style of rhetoric, the importance of sourcing and authority, and the tendency to simultaneously consider many different potential conspiracies that might underlie an important topic or event.

Indexed as

Disease OutbreaksGroup ProcessesSocial MediaZika Virus InfectionDeceptionHumansPropagandaZika Virusconspiracy theoriesrumorsocial network analysisTwitterZika virus

Identifiers

PMID30020821
PMCPMC6094351

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.