36.3802, Books: Linguistic Data Science and the English Passive: Bohmann, Müller, Honkanen, and Neuhausen (2025)

[The LINGUIST List]

LINGUIST List: Vol-36-3802. Wed Dec 10 2025. ISSN: 1069 - 4875.

Subject: 36.3802, Books: Linguistic Data Science and the English Passive: Bohmann, Müller, Honkanen, and Neuhausen (2025)

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Date: 09-Dec-2025
From: Lucy Trotter [lucy.trotter at bloomsbury.com]
Subject: Linguistic Data Science and the English Passive: Bohmann, Müller, Honkanen, and Neuhausen (2025)


Title: Linguistic Data Science and the English Passive
Subtitle: Modeling Diachronic Developments and Regional Variation
Series Title: Language, Data Science and Digital Humanities
Publication Year: 2025

Publisher: Bloomsbury Publishing
           http://www.bloomsbury.com/uk/
Book URL:
https://www.bloomsbury.com/linguistic-data-science-and-the-english-passive-9781350386549/

Author(s): Axel Bohmann, Julia Müller, Mirka Honkanen, & Miriam
Neuhausen

Hardback, ISBN: 9781350386549, £95.00

Abstract:

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.
Addressing both diachronic developments (using the Corpus of
Historical American English) and synchronic regional variation (using
the Corpus of Global Web-based English), the book employs methods that
combine traditional corpus linguistics with newer machine-learning
tools in an innovative and intricate manner. To circumscribe the
variable context, the authors train a statistical model to distinguish
central from peripheral passives. The study tests the influence of
various predictors, derived from the previous literature on the
passive, with the use of automated sentiment analysis and subject
detection, manual animacy coding, distributional semantics, and a
mixed-effects regression model.
Putting forward an automatic way of distinguishing more stative from
more dynamic passives, the book demonstrates how to examine the
passive construction in a much larger dataset than in previous
studies, and shows how advanced computational models can be used to
productively engage traditional philological questions, such as those
related to language change and regional variation.

Linguistic Field(s): Computational Linguistics
                     General Linguistics
                     Text/Corpus Linguistics




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