ArticleNature communications2025
Different honesty conceptions align across US politicians' tweets and public replies.
Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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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.
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Who cites it
2 citing papers in PubMed.
- Natural language reveals that political partisans are more affectively aligned over political issues than partisan identities.Communications psychology · 2026Article
- Tolerance for democratic norm violations increases when sincerity replaces accuracy as a marker of honesty.Communications psychology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Recent evidence shows that US politicians' conception of honesty has undergone a bifurcation, with authentic but evidence-free "belief-speaking" becoming more prominent and differentiated from evidence-based "fact-speaking". Here we examine the downstream consequences of those two ways of conceiving honesty by investigating user engagement with fact-speaking and belief-speaking texts by members of the US Congress on Twitter (now X). We measure the conceptions of honesty of a sample of tweets and replies using computational text processing, and check whether the conceptions of honesty in the tweets align with those in their replies. We find that the conceptions of honesty used in replies align with those of the tweets, suggesting a "contagion". Notably, this contagion replicates under controlled experimental conditions. Our study highlights the crucial role of political leaders in setting the tone of the conversation on social media.
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Registered trials
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.