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Different honesty conceptions align across US politicians' tweets and public replies

Author

Listed:
  • Fabio Carrella

    (University of Bristol)

  • Segun T. Aroyehun

    (University of Konstanz)

  • Jana Lasser

    (University of Graz
    Complexity Science Hub)

  • Almog Simchon

    (Ben-Gurion University of the Negev)

  • David Garcia

    (University of Konstanz
    Complexity Science Hub)

  • Stephan Lewandowsky

    (University of Bristol
    University of Potsdam)

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.

Suggested Citation

  • Fabio Carrella & Segun T. Aroyehun & Jana Lasser & Almog Simchon & David Garcia & Stephan Lewandowsky, 2025. "Different honesty conceptions align across US politicians' tweets and public replies," Nature Communications, Nature, vol. 16(1), pages 1-14, December.
    • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-56753-6
    DOI: 10.1038/s41467-025-56753-6
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    References listed on IDEAS

    as
    1. Emilio Ferrara & Zeyao Yang, 2015. "Measuring Emotional Contagion in Social Media," PLOS ONE, Public Library of Science, vol. 10(11), pages 1-14, November.
    2. Bates, Douglas & Mächler, Martin & Bolker, Ben & Walker, Steve, 2015. "Fitting Linear Mixed-Effects Models Using lme4," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 67(i01).
    3. Jana Lasser & Segun T. Aroyehun & Fabio Carrella & Almog Simchon & David Garcia & Stephan Lewandowsky, 2023. "From alternative conceptions of honesty to alternative facts in communications by US politicians," Nature Human Behaviour, Nature, vol. 7(12), pages 2140-2151, December.
    4. Mohsen Mosleh & David G. Rand, 2022. "Measuring exposure to misinformation from political elites on Twitter," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
    5. Mohsen Mosleh & David G. Rand, 2022. "Author Correction: Measuring exposure to misinformation from political elites on Twitter," Nature Communications, Nature, vol. 13(1), pages 1-1, December.
    6. Stephan Lewandowsky & Michael Jetter & Ullrich K. H. Ecker, 2020. "Using the president’s tweets to understand political diversion in the age of social media," Nature Communications, Nature, vol. 11(1), pages 1-12, December.
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