Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/307779 
Year of Publication: 
2024
Citation: 
[Journal:] Political Communication [ISSN:] 1091-7675 [Volume:] 41 [Issue:] 3 [Publisher:] Taylor & Francis [Place:] London [Year:] 2024 [Pages:] 353-372
Publisher: 
Taylor & Francis, London
Abstract: 
How do far-right actors and issues structure public debates and become mainstream over time? Previous research has shown that far-right actors are central actors in political conflicts in Western Europe, partly due to their dominance in struggles on cultural issues. The entrenchment of the far right substantially depends on their networks and public visibility. However, we still lack a long-term understanding of public debates about far-right actors and their discursive interconnections across issues. In this paper, we deliver the first longitudinal analysis of the evolution and structure of far-right discourse networks and the diffusion of far-right ideas in public debates since the 1990s. Methodologically, this paper innovates by combining discourse network analysis with automated text analysis to investigate how the relations between far-right actors and issues are represented in mass media. We analyze more than 500,000 newspaper articles in six different mass media outlets in Germany. The results show that far-right actors have gained more public visibility since the 1990s. The study demonstrates that the mass media debates have introduced and amplified cultural issues “owned” by the far right. Far-right discourse networks in mass media have grown, discursive interactions have intensified and discourse networks have become more centralized. Our results indicate that the discursive mainstreaming of the far right evolved in the context of the “refugee crisis” in 2015, and was linked to the AfD’s institutional access. Overall, the study aids in developing a better understanding of the success of the far right and the crucial role of public debates.
Subjects: 
Far right
media debate
discourse network analysis
automated text analysis
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
Document Version: 
Published Version

Files in This Item:





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.