Evidence map›Paper›PMID 37673903›Full record

ArticleScientific reports2023

A cross-lingual analysis on the spread of misinformation using the case of Ivermectin as a treatment for Covid-19.

Cameron Lai, Fujio Toriumi, Mitsuo Yoshida

Abstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Cameron LaiGraduate School of Engineering, The University of Tokyo, Tokyo, 113-0033, Japan. cameron.lai@torilab.net.
Fujio ToriumiGraduate School of Engineering, The University of Tokyo, Tokyo, 113-0033, Japan.
Mitsuo YoshidaInstitute of Business Sciences, University of Tsukuba, Tokyo, 112-0012, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The spread of misinformation transgresses international boundaries, between languages and cultures. This is especially evident in times of global crises such as the Covid-19 pandemic. This study observes misinformation on Twitter in the Japanese and English languages regarding false claims that the drug Ivermectin is an effective treatment for Covid-19. Our exploratory cross-lingual analysis identifies key themes of discussion and influential users in both languages, finding English misinformation to be highly popular amongst Japanese users. Significantly, an analysis of the timing of retweets between languages reveals that Japanese users find and widely share English misinformation often before English users themselves. This contradicts expectations that users from other languages tend to pick up on popular misinformation in English. Instead, they seek out English language sources irrespective of their popularity to support their agenda. These results emphasise the importance of cross-lingual mitigation strategies for organizations trying to combat misinformation, and that they must look beyond their own language spheres.

Indexed as

COVID-19IvermectinHumansLanguagePandemicsIvermectin

Identifiers

PMID37673903
PMCPMC10482930

What OpenQuestion holds

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LicenceCC BY
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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.