Revealing Media Bias in News Articles NLP Techniques for Automated Frame Analysis /

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 pe...

Full description

Saved in:
Bibliographic Details
Main Author: Hamborg, Felix (Author)
Corporate Author: SpringerLink (Online service)
Format: Electronic eBook
Language:English
Published: Cham : Springer Nature Switzerland : Imprint: Springer, 2023.
Edition:1st ed. 2023.
Subjects:
Online Access:Link to Metadata
Tags: Add Tag
No Tags, Be the first to tag this record!

MARC

LEADER 00000nam a22000005i 4500
001 978-3-031-17693-7
003 DE-He213
005 20240307115608.0
007 cr nn 008mamaa
008 230224s2023 sz | s |||| 0|eng d
020 |a 9783031176937  |9 978-3-031-17693-7 
024 7 |a 10.1007/978-3-031-17693-7  |2 doi 
050 4 |a QA76.9.N38 
072 7 |a UYQL  |2 bicssc 
072 7 |a COM073000  |2 bisacsh 
072 7 |a UYQL  |2 thema 
082 0 4 |a 006.35  |2 23 
100 1 |a Hamborg, Felix.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
245 1 0 |a Revealing Media Bias in News Articles  |h [electronic resource] :  |b NLP Techniques for Automated Frame Analysis /  |c by Felix Hamborg. 
250 |a 1st ed. 2023. 
264 1 |a Cham :  |b Springer Nature Switzerland :  |b Imprint: Springer,  |c 2023. 
300 |a XIII, 238 p. 30 illus., 21 illus. in color.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a text file  |b PDF  |2 rda 
505 0 |a 1. Introduction -- 2. Media Bias Analysis -- 3. Person-Oriented Framing Analysis -- 4. Target Concept Analysis -- 5. Frame Analysis -- 6. Prototype -- 7. Conclusion. . 
506 0 |a Open Access 
520 |a 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 inthe other related disciplines and understand and tackle the issue of bias from a more effective, interdisciplinary viewpoint. 
650 0 |a Natural language processing (Computer science). 
650 0 |a Machine learning. 
650 0 |a Digital media. 
650 0 |a Linguistics. 
650 0 |a Political science. 
650 1 4 |a Natural Language Processing (NLP). 
650 2 4 |a Machine Learning. 
650 2 4 |a Digital and New Media. 
650 2 4 |a Linguistics. 
650 2 4 |a Political Science. 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer Nature eBook 
776 0 8 |i Printed edition:  |z 9783031176920 
776 0 8 |i Printed edition:  |z 9783031176944 
776 0 8 |i Printed edition:  |z 9783031176951 
856 4 0 |u https://doi.org/10.1007/978-3-031-17693-7  |z Link to Metadata 
912 |a ZDB-2-SCS 
912 |a ZDB-2-SXCS 
912 |a ZDB-2-SOB 
950 |a Computer Science (SpringerNature-11645) 
950 |a Computer Science (R0) (SpringerNature-43710)