Evidence map›Paper›PMID 34025818›Full record

ArticleSocial network analysis and mining2021

COVID-19 fake news diffusion across Latin America.

Wilson Ceron, Gabriela Gruszynski Sanseverino, Mathias-Felipe de-Lima-Santos, Marcos G Quiles

Open access · bronzeAbstract readNews
In one paragraph

Article in Social network analysis and mining, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
15.5field-weighted citation impact, top 1% of its field
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

13 citing papers in PubMed, 55 citations in OpenAlex.

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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

4 authors at 3 institutions in 3 countries.

Wilson CeronFederal University of Sao Paulo, Av. Cesare Mansueto Giulio Lattes, 1201 São José dos Campos, Brazil.ORCID 0000-0002-4373-1757
Gabriela Gruszynski SanseverinoUniversity of Toulouse III - Paul Sabatier, 115d Route De Narbonne, 31077 Toulouse Cedex 4, France.
Mathias-Felipe de-Lima-SantosUniversity of Navarra, Campus Universitario s/n, Pamplona, Spain.
Marcos G QuilesFederal University of Sao Paulo, Av. Cesare Mansueto Giulio Lattes, 1201 São José dos Campos, Brazil.
Universidade Federal de São Paulo · BRUniversidad de Navarra · ESUniversité Toulouse III - Paul Sabatier · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Fact-checking verifies a multitude of claims and remains a promising solution to fight fake news. The spread of rumors, hoaxes, and conspiracy theories online is evident in times of crisis, when fake news ramped up across platforms, increasing fear and confusion among the population as seen in the COVID-19 pandemic. This article explores fact-checking initiatives in Latin America, using an original Markov-based computational method to cluster topics on tweets and identify their diffusion between different datasets. Drawing on a mixture of quantitative and qualitative methods, including time-series analysis, network analysis and in-depth close reading, our article proposes an in-depth tracing of COVID-related false information across the region, comparing if there is a pattern of behavior through the countries. We rely on the open Twitter application programming interface connection to gather data from public accounts of the six major fact-checking agencies in Latin America, namely Argentina (

Indexed as

Fact-checkingFake newsInfodemicLatin AmericaPandemicTwitter

Identifiers

PMID34025818
PMCPMC8132282
OpenAlexW3133228396

What OpenQuestion holds

Textmetadata
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.