Evidence map›Paper›PMID 40700479›Full record

ArticleScience advances2025

Understanding the success and failure of online political debate: Experimental evidence using large language models.

Tobias Heide-Jørgensen, Gregory Eady, Anne Rasmussen

Abstract read
In one paragraph

Article in Science advances, 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

3 authors.

Tobias Heide-JørgensenDepartment of Political Science, University of Copenhagen, Copenhagen 1353, Denmark.ORCID 0000-0001-7426-8307
Gregory EadyDepartment of Political Science, University of Copenhagen, Copenhagen 1353, Denmark.ORCID 0000-0003-0184-0055
Anne RasmussenDepartment of Political Science, University of Copenhagen, Copenhagen 1353, Denmark.ORCID 0000-0002-9517-3929

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Online political debate is frequently lamented for being toxic, partisan, and counterproductive. However, we know little about how core elements of political debate (justification, tone, willingness to compromise, and partisanship) affect its quality. Using text-based treatments experimentally manipulated with a large language model, we test how these elements causally affect the quality of open-text responses about issues important to the US and UK public. We find substantial evidence that differences in justification, tone, and willingness to compromise, but not partisanship, affect the quality of subsequent discourse. Combined, these elements increase the probability of high-quality responses by roughly 1.6 to 2 times and substantially increase openness to alternative viewpoints. Despite the ability to bring about substantial changes in discourse quality, we find no evidence of changes in political attitudes themselves. Our findings demonstrate how adapting approaches to online debate can foster healthy democratic interactions but have less influence on changing minds.

Indexed as

InternetLanguageModels, TheoreticalPoliticsHumansLarge Language ModelsUnited Kingdom

Identifiers

PMID40700479
PMCPMC12285710

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.