Evidence map›Paper›PMID 37223965›Full record

ArticleJMIR infodemiology2023

Global Misinformation Spillovers in the Vaccination Debate Before and During the COVID-19 Pandemic: Multilingual Twitter Study.

Jacopo Lenti, Yelena Mejova, Kyriaki Kalimeri, André Panisson, Daniela Paolotti, Michele Tizzani, Michele Starnini

Abstract read
In one paragraph

Article in JMIR infodemiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

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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

7 authors.

Jacopo LentiDepartment of Computer, Control, and Management Engineering Antonio Ruberti, Sapienza University of Rome, Rome, Italy.ORCID https://orcid.org/0000-0003-2886-7338
Yelena MejovaInstitute for Scientific Interchange Foundation, Turin, Italy.ORCID https://orcid.org/0000-0001-5560-4109
Kyriaki KalimeriInstitute for Scientific Interchange Foundation, Turin, Italy.ORCID https://orcid.org/0000-0001-8068-5916
André PanissonCENTAI Institute S.p.A., Turin, Italy.ORCID https://orcid.org/0000-0002-3336-0374
Daniela PaolottiInstitute for Scientific Interchange Foundation, Turin, Italy.ORCID https://orcid.org/0000-0003-1356-3470
Michele TizzaniInstitute for Scientific Interchange Foundation, Turin, Italy.ORCID https://orcid.org/0000-0003-3068-5111
Michele StarniniCENTAI Institute S.p.A., Turin, Italy.ORCID https://orcid.org/0000-0002-9161-5339

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAntivaccination views pervade online social media, fueling distrust in scientific expertise and increasing the number of vaccine-hesitant individuals. Although previous studies focused on specific countries, the COVID-19 pandemic has brought the vaccination discourse worldwide, underpinning the need to tackle low-credible information flows on a global scale to design effective countermeasures.

objectiveThis study aimed to quantify cross-border misinformation flows among users exposed to antivaccination (no-vax) content and the effects of content moderation on vaccine-related misinformation.

methodsWe collected 316 million vaccine-related Twitter (Twitter, Inc) messages in 18 languages from October 2019 to March 2021. We geolocated users in 28 different countries and reconstructed a retweet network and cosharing network for each country. We identified communities of users exposed to no-vax content by detecting communities in the retweet network via hierarchical clustering and manual annotation. We collected a list of low-credibility domains and quantified the interactions and misinformation flows among no-vax communities of different countries.

resultsThe findings showed that during the pandemic, no-vax communities became more central in the country-specific debates and their cross-border connections strengthened, revealing a global Twitter antivaccination network. US users are central in this network, whereas Russian users also became net exporters of misinformation during vaccination rollout. Interestingly, we found that Twitter's content moderation efforts, in particular the suspension of users following the January 6 US Capitol attack, had a worldwide impact in reducing the spread of misinformation about vaccines.

conclusionsThese findings may help public health institutions and social media platforms mitigate the spread of health-related, low-credibility information by revealing vulnerable web-based communities.

Indexed as

COVID-19misinformationsocial mediaTwittervaccination hesitancyvaccine

Identifiers

PMID37223965
PMCPMC10226529

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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.