The proximity between newspapers and political parties is strongly subjective and difficult to measure. Yet, political tendencies of newspapers can have a significant impact on voters’ opinion‐forming and ought to be known by the public in a transparent and timely manner. This article introduces the Sentiment Political Compass (SPC), a data‐driven framework for analyzing political bias of newspapers toward political parties. Using the SPC, newspapers are embedded in a two‐dimensional space (left‐leaning vs. right‐leaning, libertarian vs. autocratic). To assess the informative value of our framework, we crawled a data set consisting of 180,000 newspaper articles from twenty‐five newspapers during the German Federal Elections over a time period of 18 months and extracted 740,000 political entities enriched with their contextual sentiment. We analyze this dataset on the party‐ and politician‐level as well as considering the temporal dimension and draw insights about the relationship between newspapers and political parties. We provide the data set and our code open‐source at www.politicalcompass.de to encourage the application of the SPC to other political landscapes.

中文翻译：

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衡量报纸与政党之间的接近程度：情绪政治指南针

报纸与政党之间的距离非常主观，很难衡量。但是，报纸的政治倾向会对选民的意见形成产生重大影响，应该以透明，及时的方式让公众了解。本文介绍了情绪政治指南针（SPC）），这是一个数据驱动的框架，用于分析报纸对政党的政治偏见。使用SPC，报纸可以嵌入二维空间（左倾与右倾，自由主义者与专制）。为了评估我们框架的信息价值，我们在18个月的时间里，从德国联邦大选期间的25个报纸中抓取了由18万份报纸文章组成的数据集，并提取了74万个政治实体，丰富了他们的情境。我们在党和政客级别分析此数据集，并考虑时间维度，并得出有关报纸与政党之间关系的见解。我们在www.politicalcompass.de上提供了数据集和开放源代码，以鼓励将SPC应用于其他政治环境。