Evidence map›Paper›PMID 39543121›Full record

ArticleNature communications2024

Patterns of partisan toxicity and engagement reveal the common structure of online political communication across countries.

Max Falkenberg, Fabiana Zollo, Walter Quattrociocchi, Jürgen Pfeffer, Andrea Baronchelli

Abstract read
In one paragraph

Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 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

5 authors.

Max FalkenbergDepartment of Network & Data Science, Central European University, Vienna, Austria. max.falkenberg@protonmail.com.ORCID 0000-0002-2986-2494
Fabiana ZolloDepartment of Environmental Sciences, Informatics and Statistics, Ca' Foscari University of Venice, Venice, Italy.ORCID 0000-0002-0833-5388
Walter QuattrociocchiDepartment of Computer Science, Sapienza University of Rome, Rome, Italy.ORCID 0000-0002-4374-9324
Jürgen PfefferSchool of Social Science and Technology, Technical University of Munich, Munich, Germany.ORCID 0000-0002-1677-150X
Andrea BaronchelliDepartment of Mathematics, City St George's, University of London, London, UK. a.baronchelli.work@gmail.com.ORCID 0000-0002-0255-0829

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Existing studies of political polarization are often limited to a single country and one form of polarization, hindering a comprehensive understanding of the phenomenon. Here we investigate patterns of polarization online across nine countries (Canada, France, Germany, Italy, Poland, Spain, Turkey, UK, USA), focusing on the structure of political interaction networks, the use of toxic language targeting out-groups, and how these factors relate to user engagement. First, we show that political interaction networks are structurally polarized on Twitter (currently X). Second, we reveal that out-group interactions, defined by the network, are more toxic than in-group interactions, indicative of affective polarization. Third, we show that out-group interactions receive lower engagement than in-group interactions. Finally, we identify a common ally-enemy structure in political interactions, show that political mentions are more toxic than apolitical mentions, and highlight that interactions between politically engaged accounts are limited and rarely reciprocated. These results hold across countries and represent a step towards a stronger cross-country understanding of polarization.

Indexed as

PoliticsSocial MediaCanadaCommunicationEuropeFranceGermanyHumansItalyPolandSpainTurkeyUnited KingdomUnited States

Identifiers

PMID39543121
PMCPMC11564638

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.