Explore
Revealing Media Bias in News Articles
Felix Hamborg
2023
0 Ungluers have
Faved this Work
Login to Fave
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
This book is included in DOAB.
Why read this book? Have your say.
You must be logged in to comment.
Rights Information
Are you the author or publisher of this work? If so, you can claim it as yours by registering as an Unglue.it rights holder.Downloads
This work has been downloaded 66 times via unglue.it ebook links.
- 38 - pdf (CC BY) at Unglue.it.
- 23 - epub (CC BY) at Unglue.it.
Keywords
- artificial intelligence
- Computer science
- Computing & information technology
- content analysis
- deep learning
- Frame Analysis
- Information retrieval
- Language
- Language: history & general works
- Language: reference & general
- Machine learning
- media bias
- Media Studies
- Natural language & machine translation
- Natural Language Processing
- Political Science & Theory
- Politics & government
- Social Aspects of Computing
- Society & culture: general
- Society & Social Sciences
- thema EDItEUR::C Language and Linguistics::CB Language: reference and general::CBX Language: history and general works
- thema EDItEUR::J Society and Social Sciences::JB Society and culture: general::JBC Cultural and media studies::JBCT Media studies
- thema EDItEUR::J Society and Social Sciences::JP Politics and government::JPA Political science and theory
- thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQL Natural language and machine translation
- thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning
Links
DOI: 10.1007/978-3-031-17693-7web: https://link.springer.com/book/10.1007/978-3-031-17693-7
Editions
