This book presents a novel methodological framework for analysing governmental discourse that combines pragmatist perspectives on language with computational sociolinguistics and large language models.
This book presents a novel methodological framework for analysing governmental discourse that combines pragmatist perspectives on language with computational sociolinguistics and large language models.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Ayan-Yue Gupta has focused on research on the analysis of language and politics using computational methods, in particular natural language processing. In 2023, he completed his PhD at the University of Bristol, upon which this book is based. His current interests include computational social science, natural language processing, government discourse, polarisation and climate communications.
Inhaltsangabe
Introduction: Sociological Discourse Analysis, Natural Language Processing and Early 21st-Century Digitalisation Part 1 1. Two Approaches to the Question of Necessity 2. Semiosis, Scorekeeping and Text Systems 3. Discursive Scorekeeping and Foucault Part 2 4. Understanding Text Systems via Linguistic Variation 5. Diffusion of the Vocabulary of Crisis Neoliberalism and the Division of Labour of the British State 6. The Sociolinguistic Structure of Governmentality - Division of Labour, Division of Vocabulary, and Division of Linguistic Labour Conclusion: Comments on Piggyback Work and Future Directions
Introduction: Sociological Discourse Analysis, Natural Language Processing and Early 21st-Century Digitalisation Part 1 1. Two Approaches to the Question of Necessity 2. Semiosis, Scorekeeping and Text Systems 3. Discursive Scorekeeping and Foucault Part 2 4. Understanding Text Systems via Linguistic Variation 5. Diffusion of the Vocabulary of Crisis Neoliberalism and the Division of Labour of the British State 6. The Sociolinguistic Structure of Governmentality - Division of Labour, Division of Vocabulary, and Division of Linguistic Labour Conclusion: Comments on Piggyback Work and Future Directions
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