arXiv:2608.09936cs.CL2026-08

分析法国新闻头版如何不同地塑造左翼与右翼民粹政党的角色,发现框架存在显著不对称。

Conflict or Strategy? Asymmetric Role Framing of La France insoumise and Rassemblement National in French News Headlines, 2022-2025

  • 通过三模型大语言模型流水线分析2.8万条新闻标题,识别出政治角色框架差异。
  • 左翼激进派常被置于冲突语境,右翼民粹派则多呈现为策略性选举对手。
  • 揭示了新闻机构自身立场影响道德归因,但角色框架具跨模型稳定性。

本文研究2022至2025年间25家法语媒体发布的28,592条关于拉法国不屈(LFI)与国民联盟(RN)的新闻标题,采用三模型大语言模型流水线并经分层人工审计验证。核心发现是角色不对称而非价值不对称:冲突框架与战略博弈框架在各模型和时间跨度中均更稳健,而贬损框架较弱;‘攻击者’(AGGRESSOR)作为佐证性角色语法被广泛使用。LFI更多出现在冲突语境中,而RN则多以战略-选举语境出现。该角色差异在所有三类标注模型中方向稳定,经自助法与置换检验仍成立,并贯穿多数媒体家族及整个时期。次要的道德问责层(谁被责难、正当化或视为受害者)由媒体立场决定,掩盖了部分最极化的模式。方法上,该流水线呈现双层可靠性:冲突与战略博弈框架具有最强人工验证与跨模型一致性;行动者角色方向稳定但作为佐证因审计可靠性较低;规范性判断(合法性、责难)则表现较弱。论文提出将政治角色分配作为计算框架研究的新目标,可拆解传统价值测量所混淆的内容,并建立用于校准政治文本任务中多数投票式大语言模型流水线的结构化可靠性框架。

原文摘要 · Abstract (English)

Do French news headlines frame left- and right-populist challengers as symmetric ``extremes,'' or as fundamentally different political adversaries? We examine 28,592 headlines about La France insoumise (LFI) and Rassemblement National (RN) published by 25 French-language outlets between 2022 and 2025, annotated through a three-model LLM pipeline validated against a stratified human audit. The clearest finding is role asymmetry rather than valence asymmetry: conflict framing and strategic-game framing are more robust across models and time than delegitimization, with AGGRESSOR serving as corroborating role syntax. LFI appears in headlines more often through a conflict register and RN through a strategic-electoral register. This role gap is direction-stable across all three annotation models, survives bootstrapping and permutation tests, and persists across outlet families and most of 2022-2025. A secondary moral-accounting layer (who is blamed, legitimized, or cast as a victim) is structured by outlet rather than party, producing aggregate nulls that conceal some of the corpus's most polarized patterns. Methodologically, the annotation pipeline reveals a two-tier reliability profile: conflict and strategic-game framing achieve the strongest human validation and cross-model stability; actor role is direction-stable but treated as corroborating because its audit reliability is lower; normative-judgment constructs (legitimacy, blame) are weaker. The paper contributes political-role assignment as a target for computational framing research that decomposes what valence-based measures conflate, and establishes a construct-stratified reliability framework for calibrating majority-vote LLM annotation pipelines in political text tasks.

政治传播新闻框架大语言模型

Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品;中文卡片由大模型生成,请以原文为准。