Timo Spinde (15 results)
- Softcover
Seller: Marlton Books, Bridgeton, NJ, U.S.A.Marlton Books
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Condition: Acceptable. Readable, but has significant damage / tears. Has a remainder mark. paperback Used - Acceptable 2025.
- Softcover
Seller: Rarewaves.com USA, London, LONDO, United KingdomRarewaves.com USA
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Paperback. Condition: New. 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 shap…ing 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.
- Softcover
Seller: Books Puddle, New York, NY, U.S.A.Books Puddle
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- Softcover
Seller: Revaluation Books, Exeter, United KingdomRevaluation Books
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Paperback. Condition: Brand New. 229 pages. 8.26x5.82x8.27 inches. In Stock.
Language: English
Published by Springer Fachmedien Wiesbaden, Springer Fachmedien Wiesbaden, 2025
- Softcover
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.
- Softcover
Seller: preigu, Osnabrück, Germanypreigu
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Taschenbuch. Condition: Neu. Automated Detection of Media Bias | From the Conceptualization of Media Bias to its Computational Classification | Timo Spinde | Taschenbuch | xxvii | Englisch | 2025 | Springer | EAN 9783658477974 | Verantwortliche Person für die EU: Springer Vieweg in Springer Science + Business Media, Abraham-Linc…oln-Str. 46, 65189 Wiesbaden, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
- Softcover
Seller: Rarewaves.com UK, London, United KingdomRarewaves.com UK
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Book. Condition: New.
- Softcover
Seller: Buchpark, Trebbin, GermanyBuchpark
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Condition: Sehr gut. Zustand: Sehr gut | Seiten: 276 | Sprache: Englisch | Produktart: Bücher | 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 analy…zing 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. About the authorTimo 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.
- Softcover
- Print on Demand
Seller: Brook Bookstore On Demand, Napoli, NA, ItalyBrook Bookstore On Demand
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Condition: new. Questo è un articolo print on demand.
- Softcover
- Print on Demand
Seller: Basi6 International, Irving, TX, U.S.A.Basi6 International
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US$ 56.81
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Condition: Brand New. New. US edition. Print on demand title. Delivery takes 20-25 days.
Language: English
Published by Springer, Berlin, Springer Fachmedien Wiesbaden, Lower Saxony Ministry Of Science And Culture And The VW Foundation, Through Prof.Dr.Bela Gipp,Georg-August-Univ. Göttingen, Springer Vieweg, 2025
- Softcover
- Print on Demand
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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 ana…lyzing 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. 246 pp. Englisch.
- Softcover
- Print on Demand
Seller: Majestic Books, Hounslow, United KingdomMajestic Books
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US$ 71.71
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Condition: New. Print on Demand.
- Softcover
- Print on Demand
Seller: Biblios, frankfurt am main, HESSE, GermanyBiblios
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US$ 76.45
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Condition: New. PRINT ON DEMAND.
Language: English
Published by Springer Fachmedien Wiesbaden, Weisbaden, 2025
- Softcover
- Print on Demand
Seller: CitiRetail, Stevenage, United KingdomCitiRetail
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Paperback. Condition: new. Paperback. 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 f…actors 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. mso-ansi-language: EN-IN;">This Open Access book explores the automated identification of media bias, particularly focusing on bias by word choice in digital media. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
- Softcover
- Print on Demand
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germanybuchversandmimpf2000
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US$ 50.41
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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 analyzi…ng 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.Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 276 pp. Englisch.
