Automated Detection of Media Bias

From the Conceptualization of Media Bias to its Computational Classification
Erscheinungsjahr 2025
ISBN: 978-3-658-47797-4
Verlag: Springer

Buch, Englisch, 246 Seiten, Format (B × H): 148 mm x 210 mm, Gewicht: 361 g

This Open Access book explores the automated identification of media bias, particularly focusing on bias by word choice in digital media. The increasing prevalence of digital information presents opportunities and challenges for analyzing language, with cultural, geographic, and contextual factors shaping how content is portrayed. Despite the interdisciplinary nature of media bias research across fields like linguistics, psychology, and computer science, existing work often tackles the problem from limited perspectives, lacking comprehensive frameworks and reliable datasets. The book aims to advance the field by addressing these gaps and proposing a systematic approach to media bias detection. It develops feature-based and deep-learning approaches for automated bias detection, including a BERT-based model and MAGPIE, a multi-task learning model. These methods demonstrate improved performance on established benchmarks, showcasing the potential of deep learning in detecting media bias. Finally, the author addresses the practical applications of automated bias detection, such as enhancing news reading with forewarning messages, text annotations, and political classifiers, and examines the impact of bias on social media engagement.

Zielgruppe

Research

Autoren/Hrsg.

Spinde, Timo

Fachgebiete

• Mathematik | Informatik EDV | Informatik Professionelle Anwendung Computersimulation & Modelle, 3-D Graphik
• Sozialwissenschaften Medien- und Kommunikationswissenschaften Medienwissenschaften
• Technische Wissenschaften Technik Allgemein Modellierung & Simulation
• Sozialwissenschaften Medien- und Kommunikationswissenschaften Kommunikationswissenschaften
• Mathematik | Informatik EDV | Informatik Angewandte Informatik

Inhaltsverzeichnis

Introduction.- Media Bias.- Questionnaire Development.- Dataset Creation.- Feature-based Media Bias Detection.- Neural Media Bias Detection.- Visualization and Perception of Media Bias.- Conclusion and FutureWork.

Über Autor(innen)

Timo Spinde is a postdoctoral researcher specializing in media bias. He is the founder and coordinator of the Media Bias Group research network. He is affiliated with the University of Göttingen and the National Institute of Informatics (NII) in Tokyo.