Linguistic data science and the English passive: modelling diachronic developments and regional variation
The choice between BE and GET as auxiliary verbs, as in “She was promoted” vs “She got promoted”, is a central, grammatical feature, yet the many proposed nuances conditioning this phenomenon have escaped large-scale empirical validation to date. This book fills this gap, using multivariate statisti...
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| Hauptverfasser: | , , , |
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| Dokumenttyp: | Buch/Monographie |
| Sprache: | Englisch |
| Veröffentlicht: |
London
Bloomsbury Academic
2025
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| Ausgabe: | Erstausgabe |
| Schriftenreihe: | Language, Data Science and Digital Humanities
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| Online-Zugang: |
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| Verfasserangaben: | Axel Bohrmann, Julia Müller, Mirka Hokanen and Miriam Neuhausen |
MARC
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| 245 | 0 | 0 | |a Linguistic data science and the English passive |b modelling diachronic developments and regional variation |c Axel Bohrmann, Julia Müller, Mirka Hokanen and Miriam Neuhausen |
| 250 | |a Erstausgabe | ||
| 264 | 1 | |a London |b Bloomsbury Academic |c 2025 | |
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| 490 | 0 | |a Language, Data Science and Digital Humanities | |
| 500 | |a Literaturverzeichnis: Seiten [237]-264 | ||
| 520 | |a The choice between BE and GET as auxiliary verbs, as in “She was promoted” vs “She got promoted”, is a central, grammatical feature, yet the many proposed nuances conditioning this phenomenon have escaped large-scale empirical validation to date. This book fills this gap, using multivariate statistical analyses of several large corpora to explore different factors determining the choice of English passive auxiliary. | ||
| 520 | |a Introduction 1. The English Passive Voice -- 2. Centrality and the Passive Gradient -- 3. Operationalising Subject Responsibility -- 4. Operationalising Adversativity and Non-Neutrality -- 5. Distributional Verb Semantics -- 6. The Structure of the Proposed Models -- 7. Diachronic Developments in the Passive -- 8. Regional Variation in the Passive -- 9. Conclusion -- References -- Index | ||
| 520 | |a "Filling a gap in existing research, this book employs multivariate statistical analyses of several large corpora to explore different factors determining the choice of English passive auxiliary. Addressing both diachronic developments and synchronic regional variation, it combines traditional corpus linguistics with newer machine-learning tools, testing the influence of various predictors with the use of automated sentiment analysis and subject detection, manual animacy coding, distributional semantics, and a mixed-effects regression model"-- Provided by publisher | ||
| 650 | 0 | |a English language |x Passive voice |0 http://id.loc.gov/authorities/subjects/sh85043635 |2 DLC | |
| 650 | 0 | |a English language |x Variation |0 http://id.loc.gov/authorities/subjects/sh85043757 |2 DLC | |
| 650 | 0 | |a Corpora (Linguistics) |x Data processing |2 DLC | |
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| 700 | 1 | |a Müller, Julia |e VerfasserIn |0 (DE-588)136760513X |0 (DE-627)192731335X |4 aut | |
| 700 | 1 | |a Honkanen, Mirka |e VerfasserIn |0 (DE-588)1217071555 |0 (DE-627)1728873169 |4 aut | |
| 700 | 1 | |a Neuhausen, Miriam |e VerfasserIn |0 (DE-588)1350010448 |0 (DE-627)1910563897 |4 aut | |
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