Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 448

The DOI matches its Crossref record; 23 of the 23 references it cites were found in a registry or an index.

COVID-19 infodemic: More retweets for science-based information on coronavirus than for false information

Open access
Pulido, Cristina M, Villarejo-Carballido, Beatriz, Redondo-Sama, Gisela, Gómez, Aitor·2020·International Sociology

Abstract

The World Health Organization has not only signaled the health risks of COVID-19, but also labeled the situation as infodemic, due to the amount of information, true and false, circulating around this topic. Research shows that, in social media, falsehood is shared far more than evidence-based information. However, there is less research analyzing the circulation of false and evidence-based information during health emergencies. Thus, the present study aims at shedding new light on the type of tweets that circulated on Twitter around the COVID-19 outbreak for two days, in order to analyze how false and true information was shared. To that end, 1000 tweets have been analyzed. Results show that false information is tweeted more but retweeted less than science-based evidence or fact-checking tweets, while science-based evidence and fact-checking tweets capture more engagement than mere facts. These findings bring relevant insights to inform public health policies.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1177/0268580920914755

Cites

23 of 23 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 23 references

Cited by

See all 448

Metadata

Authors
Pulido, C. M., Villarejo-Carballido, B., Redondo-Sama, G., & Gómez, A.
Venue
International Sociology
Published
2020-04-15
Volume
35
Issue
4
Pages
377-392
ISSN
  • 0268-5809 (ISSN-L)
  • 1461-7242
OpenAlex
W3015998441
Cited by
448
References
23
FWCI
120.97
Type
journal article
Language
en
Open access
hybrid

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: COVID-19 infodemic: More retweets for science-based information on coronavirus than for false information. https://app.cochat.ai/papers/10.1177/0268580920914755
The paper
Pulido, C. M., Villarejo-Carballido, B., Redondo-Sama, G., & Gómez, A. (2020). COVID-19 infodemic: More retweets for science-based information on coronavirus than for false information. International Sociology. https://doi.org/10.1177/0268580920914755

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.