Evidence map›Paper›PMID 34459833›Full record

ArticleJMIRx med

Social Media Polarization and Echo Chambers in the Context of COVID-19: Case Study.

Julie Jiang, Xiang Ren, Emilio Ferrara

Abstract read
In one paragraph

Article in JMIRx med. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

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

  1. Pooled it
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  5. A Risk Taxonomy and Reflection Tool for Large Language Model Adoption in Public Health.Proceedings of the ACM on human-computer interaction · 2025
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  6. Political identity and risk politics: Evidence from a pandemic.Risk analysis : an official publication of the Society for Risk Analysis · 2025
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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

3 authors.

Julie JiangInformation Sciences Institute University of Southern California Marina Del Rey, CA United States.ORCID https://orcid.org/0000-0003-4260-282X
Xiang RenDepartment of Computer Science Viterbi School of Engineering University of Southern California Los Angeles, CA United States.ORCID https://orcid.org/0000-0001-8655-663X
Emilio FerraraInformation Sciences Institute University of Southern California Marina Del Rey, CA United States.ORCID https://orcid.org/0000-0002-1942-2831

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSocial media chatter in 2020 has been largely dominated by the COVID-19 pandemic. Existing research shows that COVID-19 discourse is highly politicized, with political preferences linked to beliefs and disbeliefs about the virus. As it happens with topics that become politicized, people may fall into echo chambers, which is the idea that one is only presented with information they already agree with, thereby reinforcing one's confirmation bias. Understanding the relationship between information dissemination and political preference is crucial for effective public health communication.

objectiveWe aimed to study the extent of polarization and examine the structure of echo chambers related to COVID-19 discourse on Twitter in the United States.

methodsFirst, we presented Retweet-BERT, a scalable and highly accurate model for estimating user polarity by leveraging language features and network structures. Then, by analyzing the user polarity predicted by Retweet-BERT, we provided new insights into the characterization of partisan users.

resultsWe observed that right-leaning users were noticeably more vocal and active in the production and consumption of COVID-19 information. We also found that most of the highly influential users were partisan, which may contribute to further polarization. Importantly, while echo chambers exist in both the right- and left-leaning communities, the right-leaning community was by far more densely connected within their echo chamber and isolated from the rest.

conclusionsWe provided empirical evidence that political echo chambers are prevalent, especially in the right-leaning community, which can exacerbate the exposure to information in line with pre-existing users' views. Our findings have broader implications in developing effective public health campaigns and promoting the circulation of factual information online.

Indexed as

case studycommunicationCOVID-19echo chamberinfodemiologyinfoveillanceopinionpolarizationsocial mediaTwitter

Identifiers

PMID34459833
PMCPMC8371575

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.