Evidence map›Paper›PMID 41262979›Full record

ArticlePNAS nexus2025

Post-January 6 deplatforming shows long-term effects on ideological polarization among Twitter users.

Cody Buntain, Maria Snegovaya

Abstract read
In one paragraph

Article in PNAS nexus, 2025. 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

2 authors.

Cody BuntainCollege of Information Studies, University of Maryland, 130 Campus Dr 4th Floor, College Park, MD 20742, USA.ORCID https://orcid.org/0000-0003-4797-3726
Maria SnegovayaEdmund A. Walsh School of Foreign Service, Georgetown University, CC 301, 37th St NW & O St NW, Washington, DC 20057, USA.ORCID https://orcid.org/0000-0002-7979-5672

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study examines audience response to Twitter's "Great Deplatforming" following the January 6 attack on the US Capitol. Using a survey of Twitter users from the 2020 US election, we test whether Twitter's deplatforming coincides with significant changes in respondents' behavior, operationalized using individuals' posting frequency and ideological lean-measured daily via a news-sharing metric we validate. To control for exogenous changes in the information environment, we pair Twitter respondents with Reddit accounts that exhibit similar pre-event behavior. Results indicate a shift in Twitter's ideological landscape: Respondents become more extreme, and polarization between liberals and conservatives intensifies as ideologically extreme users move further from the center. As the Great Deplatforming recedes, our Twitter users trend toward the center, suggesting that, while the platform experiences an immediate shock, it ultimately undergoes a long-term moderating effect. Importantly, these effects do not appear on Reddit, which instead exhibits an immediate reduction in ideological extremity following January 6th and sees no changes in longer-term trends. We also do not find evidence of a uniform flight from Twitter; only conservative-leaning respondents are significantly less likely to remain active. While results show ideologically extreme Twitter accounts experience some suppressive effect in activity, these effects seem specific to the most extreme actors, as decreasing trends among middle-of-the-road actors are present in both Twitter and Reddit. Taken together, while Twitter did experience a significant increase in the level of polarization and ideological extremity, the long-term trend appears to be one of moderation, an effect absent from Reddit.

Indexed as

deplatformingdifferential effectspolarization

Identifiers

PMID41262979
PMCPMC12624514

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.