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Red and blue language: Word choices in the Trump & Harris 2024 presidential debate

arXiv 2410.13654 ↗First posted 17 Oct 2024cs.CLcited by 0

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Abstract (arXiv)

Political debates are a peculiar type of political discourse, in which candidates directly confront one another, addressing not only the the moderator's questions, but also their opponent's statements, as well as the concerns of voters from both parties and undecided voters. Therefore, language is adjusted to meet specific expectations and achieve persuasion. We analyse how the language of Trump and Harris during the debate (September 10th 2024) differs in relation to the following semantic and pragmatic features, for which we formulated targeted hypotheses: framing values and ideology, appealing to emotion, using words with different degrees of concreteness and specificity, addressing others through singular or plural pronouns. Our findings include: differences in the use of figurative frames (Harris often framing issues around recovery and empowerment, Trump often focused on crisis and decline); similar use of emotional language, with Trump showing a slight higher tendency toward negativity and toward less subjective language compared to Harris; no significant difference in the specificity of candidates' responses; similar use of abstract language, with Trump showing more variability than Harris, depending on the subject discussed; differences in addressing the opponent, with Trump not mentioning Harris by name, while Harris referring to Trump frequently; different uses of pronouns, with Harris using both singular and plural pronouns equally, while Trump using more singular pronouns. The results are discussed in relation to previous literature on Red and Blue language, which refers to distinct linguistic patterns associated with conservative (Red) and liberal (Blue) political ideologies.

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References · 6

  1. 2023GPT-4 Technical Reportcited by 18,396
  2. 2024LLMs instead of Human Judges? A Large Scale Empirical Study across 20 NLP Evaluation Taskscited by 243
  3. 2024Political DEBATE: Efficient Zero-shot and Few-shot Classifiers for Political Textcited by 8
  4. 2024Human Interest or Conflict? Leveraging LLMs for Automated Framing Analysis in TV Showscited by 5
  5. 2024Exploring Spatial Schema Intuitions in Large Language and Vision Modelscited by 4
  6. 2015Mimicry Is Presidential: Linguistic Style Matching in Presidential Debates and Improved Polling Numberscited by 2

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