全球危机与国家政策：德语在线媒体政治内容的大规模分析
Global Crises and National Policies: A Large Scale Analysis of Political Content in German Language Online Media
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中文总结 AI 辅助
本研究分析2019-2022年德语在线媒体的数百万篇文章和推文，发现国际危机可同步传统媒体政治内容，其自动化政治分析能提升媒体透明度与公共话语平衡性。
中文摘要 AI 辅助
如今，大多数媒体内容是基于算法推荐进行消费的。有证据表明，这可能会导致政治偏向性的媒体消费模式。从文本中自动提取政治议程可以揭示和分析在线媒体中的政治偏向，从而有助于促进无政治偏向的媒体消费。在此，我们采用现代政治文本分析方法，展示了在线媒体中自动化细粒度政治偏向分析的潜力。我们对2019-2022年期间德语在线媒体中的政治内容进行了分析，涵盖了数百万篇文章和推文，涉及具有全球和国家层面深远社会影响的事件，包括COVID-19大流行和乌克兰战争的开端。我们的分析确定了国家（德国和瑞士）报道之间的主题相似性，特别是在受国际事件驱动的类别中。我们还发现，在受国内影响的类别中出现了分歧，这反映了国家政策和制度结构的差异。对报纸和Twitter话语的比较显示，在大流行期间，两种媒体围绕共同核心趋同，但在强度和时间动态方面存在差异。报纸表现出更稳定的政治内容，而Twitter则通过短暂的事件驱动峰值做出反应。这些发现表明，国际危机对传统媒体中的政治内容具有强大的同步作用，暂时超越了国家和媒体形式的差异。我们的自动化政治分析通过使在线媒体中的政治议程透明化，赋予公民权力。这种透明度还使媒体机构能够弥合算法驱动的回音室与更知情、更平衡的公共话语之间的差距。
英文摘要
Today most media content is consumed based on algorithmic recommendations. Evidence suggests that this can lead to politically biased media consumption patterns. Automated extraction of political agendas from texts can reveal and analyze political biases in online media -- and thus help fostering politically unbiased media consumption. Here we employ modern political text analysis methods demonstrating the potential of automated fine-grained political bias analysis in online media. We conduct an analysis of political content in German language online media during the period 2019--2022, encompassing several million articles and tweets covering events with profound societal impact globally and nationally, the COVID-19 pandemic and the beginning of the war in Ukraine. Our analysis identifies thematic similarity between national (German and Swiss) reporting, particularly for categories driven by international events. We also find divergences emerging in domestically influenced categories, reflecting differences in national policies and institutional structures. A comparison of newspaper and Twitter discourse reveals that both media converge around a shared core during the pandemic, yet differ in intensity and temporal dynamics. Newspapers exhibit more stable political content, while Twitter reacts through short-lived event-driven spikes. These findings indicate that international crises act as a powerful synchronizing force on political content in classical media, temporarily overriding both national and media-form differences. Our automated political analysis empowers citizens by rendering political agendas in online media transparent. This transparency also enables media outlets to bridge the gap between algorithm-driven echo chambers and a more informed, balanced public discourse.
发表机构
- Berliner Hochschule für Technik（柏林技术高等学院）
- Einstein Center Digital Future（爱因斯坦数字未来中心）
机构由 AI 辅助整理，请以论文原文为准。
