[论文解读] Cross-National Evidence of Disproportionate Media Visibility for the Radical Right in the 2024 European Elections

Íris Damião, João Franco+4 more|arXiv (Cornell University)|Jan 9, 2026

Social Media and Politics被引用 0

一句话总结

该论文对跨越五个欧洲国家的约21,500篇在线新闻文章进行系统分析，显示相对选举表现，极端右翼在媒体曝光度上得到的关注不成比例且在各国之间 Pattern 稳定，并在最后竞选阶段加剧。

ABSTRACT

This study provides a systematic comparative analysis of media visibility of different political families during the 2024 European Parliament elections. We analyzed close to 21,500 unique news from leading national outlets in Austria, Germany, Ireland, Poland, and Portugal - countries with diverse political contexts and levels of media trust. Combining computational and human classification, we identified parties, political leaders, and groups from the article's URLs and titles, and clustered them according to European Parliament political families and broad political leanings. Cross-country comparison shows that the Mainstream and the Radical Right were mentioned more often than the other political groups. Moreover, the Radical Right received disproportionate attention relative to electoral results (from 2019 or 2024) and electoral projections, particularly in Austria, Germany, and Ireland. This imbalance increased in the final weeks of the campaign, when media influence on undecided voters is greatest. Outlet-level analysis shows that coverage of right-leaning entities dominated across news sources, especially those generating the highest traffic, suggesting a structural rather than outlet-specific pattern. Media visibility is a central resource, and this systematic mapping of online coverage highlights how traditional media can contribute to structural asymmetries in democratic competition.

研究动机与目标

• 评估五个欧洲国家在2024年欧洲议会选举前，媒体对政治家族的曝光度如何变化。
• 识别在线新闻中被提及最多的政治倾向以及其与选举结果和民调的相关性。
• 将国家政党映射到欧洲议会团体和广义思想倾向，以比较跨国模式。

提出的方法

• 使用 Media Cloud 构建奥地利、爱尔兰、德国、波兰和葡萄牙在2024年欧盟选举前两个月的综合在线新闻数据库。
• 通过大语言模型提取（ChatGPT-4o）和模糊匹配，在新闻标题和URL中识别政治实体（政治家、政党、倾向），并进行人工验证。
• 将国家政党映射到2019–2024年欧洲议会团体及10个意识形态类别，然后按五个广义倾向汇总提及：激进左派、主流左派、绿色派、主流右派、激进右派。
• 计算各国按倾向的提及比例，并基于席位对跨国进行加权平均。
• 将提及频次与2019年结果、选前民调和2024年结果进行比较；使用标准差阈值评估偏差。

Figure 2: Methodological Pipeline - News Collection. Media Sources were selected from Semrush Top 20 Newspapers for each country and excluding social media and search engine pages (e.g., “YouTube.com”). News articles were collected from these sources using two sets of queries (yellow and blue), deri

实验结果

研究问题

• RQ1 在2024年欧盟选举期间，每个国家五大广义政治倾向的媒体提及分布如何？
• RQ2 激进右翼实体是否相对于先前代表性或预期选举表现获得不成比例的媒体关注，这种情况是否因国家和时间而异？
• RQ3 媒体曝光与选举结果及民调之间的关系如何，是否存在提示结构性媒体偏见的跨国模式？
• RQ4 在将国家政党映射到欧洲议会团体与更广义的意识形态类别时，倾向分类的鲁棒性如何？

主要发现

• 激进右翼实体在各国的提及次数高于其他群体，与2019年和2024年的结果相比存在不成比例的关注。
• 即使在没有议会代表的爱尔兰，激进右翼也成为最常被提及的群体之一。
• 报道对右倾实体的覆盖在各媒体与国家中占主导，尤其是在高流量来源中，显示出一种结构性模式而非特定媒体偏见。
• 在竞选最后阶段，媒体对未决 voters 的影响最大时，这种不成比例的曝光度进一步加强。
• 本研究分析了五国顶级媒体的21,528条新闻，采用综合的LLM与模糊匹配方法并辅以人工验证，将政治实体与欧洲团体及意识形态对齐。

Figure 3: Methodological Pipeline - Entities Extraction. A) All news headlines and their respective URLs were processed using the ChatGPT-4o API to identify political entities – such as politicians (e.g., Hildergard Bentele), political parties (e.g., AfD), and political leanings (e.g., the left). B)