Timo spinde (14 résultats)
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Vendeur : Marlton Books, Bridgeton, NJ, Etats-UnisMarlton Books
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Paperback. Etat : 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 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.
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Vendeur : Books Puddle, New York, NY, Etats-UnisBooks Puddle
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Paperback. Etat : Brand New. 229 pages. 8.26x5.82x8.27 inches. In Stock.
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Langue : anglais
Edité par Springer Fachmedien Wiesbaden, Springer Fachmedien Wiesbaden, 2025
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Vendeur : AHA-BUCH GmbH, Einbeck, AllemagneAHA-BUCH GmbH
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Taschenbuch. Etat : 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, wit…h 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.
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Vendeur : preigu, Osnabrück, Allemagnepreigu
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EUR 41,45
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Taschenbuch. Etat : 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-Lincoln-…Str. 46, 65189 Wiesbaden, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Vendeur : Rarewaves.com UK, London, Royaume-UniRarewaves.com UK
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EUR 47,89
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Vendeur : Buchpark, Trebbin, AllemagneBuchpark
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Etat : 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 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. 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.
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Vendeur : Brook Bookstore On Demand, Napoli, NA, ItalieBrook Bookstore On Demand
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Etat : new. Questo è un articolo print on demand.
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Vendeur : Basi6 International, Irving, TX, Etats-UnisBasi6 International
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EUR 53,35
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Etat : Brand New. New. Delivery takes 20-25 days. Print on Demand.
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Langue : anglais
Edité par 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
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Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AllemagneBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Etat : 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 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. 246 pp. Englisch.
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Vendeur : Majestic Books, Hounslow, Royaume-UniMajestic Books
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Vendeur : Biblios, frankfurt am main, HESSE, AllemagneBiblios
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EUR 64,12
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Etat : New. PRINT ON DEMAND.
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Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagnebuchversandmimpf2000
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Taschenbuch. Etat : 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 analyzing l…anguage, 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.
