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

Area of Science:

• Political Communication
• Computational Social Science
• Social Media Analysis

Background:

• US politicians' understanding of honesty has bifurcated into "belief-speaking" (authentic, evidence-free) and "fact-speaking" (evidence-based).
• The prominence of "belief-speaking" suggests a shift in political communication strategies.
• Understanding the impact of these communication styles on public engagement is crucial.

Purpose of the Study:

• To investigate the downstream consequences of "belief-speaking" and "fact-speaking" on user engagement.
• To examine how honesty conceptions in US Congressional communications on Twitter (now X) influence user replies.
• To determine if these communication patterns are contagious and replicable under controlled conditions.

Main Methods:

• Computational text processing to measure conceptions of honesty in a sample of tweets and replies from US Congress members.
• Analysis of alignment between honesty conceptions in original tweets and subsequent user replies.
• Controlled experimental conditions to test the replicability of observed engagement patterns.

Main Results:

• A significant alignment was found between the conceptions of honesty in tweets and their replies, suggesting a "contagion" effect.
• This contagion effect was replicated under controlled experimental settings.
• Political leaders' communication styles significantly influence the tone and nature of social media conversations.

Conclusions:

• The way politicians frame honesty in their communications directly impacts how social media users engage with political content.
• Political leaders play a pivotal role in shaping the discourse on social media platforms.
• The findings underscore the importance of evidence-based communication in political discourse.