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Gendered Communication Patterns of Political Elites on Truth Social

Tom Bidewell, Artemis Deligianni, Tuğrulcan Elmas, Clare Llewellyn, Björn Ross

Abstract

The influence of gender on online political communication remains contested, with existing scholarship providing mixed evidence as to whether gender shapes political messaging in digital environments. However, this debate has largely centred on mainstream platforms such as X (formerly Twitter), leaving the dynamics of alt-tech social media underexamined. This paper addresses this gap by analysing gendered patterns of political communication on Truth Social, a hyper-partisan platform that functions as a hub for the most committed followers of the American far right, a community closely associated with hegemonic masculine norms. To address this gap, we present the first large-scale analysis of political elite communication on Truth Social, using a novel dataset of 107k posts from 129 U.S. political figures. We examine the extent to which gender influences rhetorical style, topic framing, and audience engagement. We find that many gendered communication patterns documented on mainstream platforms persist on Truth Social. In particular, women political elites tend to express more joy and less anger than men and receive significantly higher levels of audience engagement. At the same time, more nuanced differences emerge. Although men and women political elites discuss largely similar conservative themes, they differ in how these issues are framed and in the rhetorical strategies employed. Notably, posts associated with women political elites contain higher levels of fear-based rhetoric, potentially suggesting selective adaptation in communicative style to navigate gender norms on the platform. These findings suggest that on Truth Social, an alt-tech platform with distinct ideological characteristics, mainstream gendered constraints persist, but are expressed through platform-specific communicative patterns shaped by its partisan orientation and sociotechnical environment.

Gendered Communication Patterns of Political Elites on Truth Social

Abstract

The influence of gender on online political communication remains contested, with existing scholarship providing mixed evidence as to whether gender shapes political messaging in digital environments. However, this debate has largely centred on mainstream platforms such as X (formerly Twitter), leaving the dynamics of alt-tech social media underexamined. This paper addresses this gap by analysing gendered patterns of political communication on Truth Social, a hyper-partisan platform that functions as a hub for the most committed followers of the American far right, a community closely associated with hegemonic masculine norms. To address this gap, we present the first large-scale analysis of political elite communication on Truth Social, using a novel dataset of 107k posts from 129 U.S. political figures. We examine the extent to which gender influences rhetorical style, topic framing, and audience engagement. We find that many gendered communication patterns documented on mainstream platforms persist on Truth Social. In particular, women political elites tend to express more joy and less anger than men and receive significantly higher levels of audience engagement. At the same time, more nuanced differences emerge. Although men and women political elites discuss largely similar conservative themes, they differ in how these issues are framed and in the rhetorical strategies employed. Notably, posts associated with women political elites contain higher levels of fear-based rhetoric, potentially suggesting selective adaptation in communicative style to navigate gender norms on the platform. These findings suggest that on Truth Social, an alt-tech platform with distinct ideological characteristics, mainstream gendered constraints persist, but are expressed through platform-specific communicative patterns shaped by its partisan orientation and sociotechnical environment.
Paper Structure (18 sections, 5 figures)

This paper contains 18 sections, 5 figures.

Table of Contents

  1. Introduction
  2. Related Work
  3. Data
  4. Exploratory Data Analysis
  5. Methods
  6. Content
  7. Rhetorical Style
  8. Audience Responses
  9. Gender and Statistical Analyses
  10. Results
  11. RQ1: Content
  12. RQ2: Rhetorical Style
  13. RQ3: Audience Responses
  14. Discussion
  15. Limitations
  16. ...and 3 more sections

Figures (5)

  • Figure 1: Predicted probabilities of using each of the 5 emotionsfor men and women political elites. The error bars indicate 95% Credible Intervals. Each sub-figure represents the estimated gender probabilities of using that emotion based on the respective Logistic Regression model fitted. For sadness and fear, we do not find evidence gender predicting their use in posts (Sub-figures D and E).
  • Figure 2: Estimated counts of replies received by men and by women political elites to their posts when controlling for covariates. Errorbars indicate 95% Credible Intervals.
  • Figure 3: Interaction of gender and political position for reply counts. Estimates are predicted counts of replies received by posts of political elites depending on their gender and political position. Errorbars indicate 95% Credible Intervals.
  • Figure 4: Estimated counts of upvotes received by men and by women to their posts when controlling for covariates. Errorbars indicate 95% Credible Intervals.
  • Figure 5: Interaction of gender and political position for upvote counts. Estimates are predicted counts of replies received by posts of political elites depending on their gender and political position. Errorbars indicate 95% Credible Intervals.