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Annotated Spanish general election debate transcriptions 1993-2023.

Fermín L Cruz1, Fernando Enríquez2, F Javier Ortega3

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Summary

This study introduces the DebatES dataset, a comprehensive Spanish election debate resource. It enables advanced analysis of political discourse, persuasive strategies, and polarization using NLP and LLM annotations.

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Area of Science:

  • Computational Linguistics
  • Political Science
  • Language Technologies

Background:

  • Automatic analysis of political discourse needs specialized resources, especially for non-English debates.
  • Spanish electoral debates present unique characteristics compared to parliamentary sessions.

Purpose of the Study:

  • To introduce the DebatES dataset, a novel resource for analyzing Spanish televised general election debates.
  • To provide manually reviewed transcriptions with rich annotations for linguistic and political analysis.

Main Methods:

  • Manual transcription and review of nearly all Spanish national televised general election debates since 1993.
  • Segmentation of transcripts into turns and thematic blocks with participant metadata.
  • Enrichment with linguistic-stylistic metrics via NLP and annotations (topics, emotions, entities, proposals, claims) using LLMs and manual validation.

Main Results:

  • The DebatES dataset contains segmented transcripts with participant metadata.
  • Annotations include turn topics, emotions, entities, electoral proposals, and factual claims.
  • Data is available in standard formats (XML, CSV) with interactive reports.

Conclusions:

  • The DebatES dataset is a valuable, accessible resource for researchers in linguistics, political science, and language technologies.
  • It facilitates the study of discourse evolution, persuasive strategies, and ideological polarization in Spanish politics.