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  • © 2023

Revealing Media Bias in News Articles

NLP Techniques for Automated Frame Analysis

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  • This book is open access, which means that you have free and unlimited access
  • Presents an interdisciplinary approach to reveal biases in English news articles reporting on a given political event
  • Introduces person-oriented framing analysis, an approach assessing how articles portray persons involved in the event
  • Combines approaches from computer science, computational linguistics, and political science

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Table of contents (7 chapters)

  1. Front Matter

    Pages i-xiii
  2. Introduction

    • Felix Hamborg
    Pages 1-10Open Access
  3. Media Bias Analysis

    • Felix Hamborg
    Pages 11-53Open Access
  4. Person-Oriented Framing Analysis

    • Felix Hamborg
    Pages 55-70Open Access
  5. Target Concept Analysis

    • Felix Hamborg
    Pages 71-108Open Access
  6. Frame Analysis

    • Felix Hamborg
    Pages 109-140Open Access
  7. Prototype

    • Felix Hamborg
    Pages 141-181Open Access
  8. Conclusion

    • Felix Hamborg
    Pages 183-199Open Access
  9. Back Matter

    Pages 201-238

About this book

This open access book presents an interdisciplinary approach to reveal biases in English news articles reporting on a given political event. The approach named person-oriented framing analysis identifies the coverage’s different perspectives on the event by assessing how articles portray the persons involved in the event. In contrast to prior automated approaches, the identified frames are more meaningful and substantially present in person-oriented news coverage.

The book is structured in seven chapters: Chapter 1 presents a few of the severe problems caused by slanted news coverage and identifies the research gap that motivated the research described in this thesis. Chapter 2 discusses manual analysis concepts and exemplary studies from the social sciences and automated approaches, mostly from computer science and computational linguistics, to analyze and reveal media bias. This way, it identifies the strengths and weaknesses of current approaches for identifying and revealing media bias. Chapter 3 discusses the solution design space to address the identified research gap and introduces person-oriented framing analysis (PFA), a new approach to identify substantial frames and to reveal slanted news coverage. Chapters 4 and 5 detail target concept analysis and frame identification, the first and second component of PFA. Chapter 5 also introduces the first large-scale dataset and a novel model for target-dependent sentiment classification (TSC) in the news domain. Eventually, Chapter 6 introduces Newsalyze, a prototype system to reveal biases to non-expert news consumers by using the PFA approach. In the end, Chapter 7 summarizes the thesis and discusses the strengths and weaknesses of the thesis to derive ideas for future research on media bias.

This book mainly targets researchers and graduate students from computer science, computational linguistics, political science, and further social sciences who want to get an overview of the relevant state of the art in the other related disciplines and understand and tackle the issue of bias from a more effective, interdisciplinary viewpoint.

Authors and Affiliations

  • Department of Computer Science, Humboldt University of Berlin, Berlin, Germany

    Felix Hamborg

About the author

Felix Hamborg is a research group leader at the Heidelberg Academy of Sciences and Humanities and a visiting researcher at the Humboldt University of Berlin, Germany. His research focuses on the automated identification of media bias in news articles and combines approaches from deep learning, natural language processing, information visualization, and political science. He completed his PhD at the University of Konstanz and was awarded several Best Paper / Outstanding Paper awards at renowned conferences like JCDL, CIKM, or the iConference. 

Bibliographic Information

  • Book Title: Revealing Media Bias in News Articles

  • Book Subtitle: NLP Techniques for Automated Frame Analysis

  • Authors: Felix Hamborg

  • DOI: https://doi.org/10.1007/978-3-031-17693-7

  • Publisher: Springer Cham

  • eBook Packages: Computer Science, Computer Science (R0)

  • Copyright Information: The Editor(s) (if applicable) and The Author(s) 2023

  • Hardcover ISBN: 978-3-031-17692-0Published: 26 February 2023

  • Softcover ISBN: 978-3-031-17695-1Published: 26 February 2023

  • eBook ISBN: 978-3-031-17693-7Published: 24 February 2023

  • Edition Number: 1

  • Number of Pages: XIII, 238

  • Number of Illustrations: 9 b/w illustrations, 21 illustrations in colour

  • Topics: Natural Language Processing (NLP), Machine Learning, Digital/New Media, Linguistics, general, Political Science

Buy it now

Buying options

Softcover Book USD 49.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 59.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access