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Measuring Proximity Between Newspapers and Political Parties: The Sentiment Political Compass
Author(s) -
Falck Fabian,
Marstaller Julian,
Stoehr Niklas,
Maucher Sören,
Ren Jeana,
Thalhammer Andreas,
Rettinger Achim,
Studer Rudi
Publication year - 2020
Publication title -
policy and internet
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.281
H-Index - 26
ISSN - 1944-2866
DOI - 10.1002/poi3.222
Subject(s) - newspaper , politics , autocracy , political science , german , political communication , dimension (graph theory) , set (abstract data type) , public opinion , democracy , computer science , law , history , mathematics , archaeology , pure mathematics , programming language
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.