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Cited by 623

The DOI matches its Crossref record; 377 of the 377 references it cites were found in a registry or an index.

Register, Genre, and Style

Biber, Douglas, Conrad, Susan·2019·Cambridge University Press eBooks

Abstract

A fully updated and expanded second edition of this flagship work, which introduces methodological techniques to carry out analyses of text varieties, and provides descriptions of the most important text varieties in English. Part I introduces an analytical framework for studying registers, genre conventions, and styles, while Part II provides more detailed corpus-based descriptions of text varieties in English, including spoken interpersonal varieties, general and professional written varieties and emerging electronic varieties. Part III introduces more advanced analytical approaches and deals with larger theoretical concerns, such as the relationship between register studies and other sub-disciplines of linguistics, and practical applications of register analysis. A new chapter on EAP and ESP has been added, with new sections on the important differences between academic writing in the humanities and sciences, and a case study on engineering reports as an ESP register and genre. Coverage of new electronic registers has been updated, and a new analysis of hybrid registers has been added.

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Crossref · 10.1017/9781108686136

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Metadata

Authors
Biber, D., & Conrad, S.
Venue
Cambridge University Press eBooks
Published
2019-05-08
OpenAlex
W3127589626
Cited by
623
References
377
FWCI
148.36
Type
book
Language
en
Open access
closed

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CoChat. (2026). Citation check: Register, Genre, and Style. https://app.cochat.ai/papers/10.1017/9781108686136
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Biber, D., & Conrad, S. (2019). Register, Genre, and Style. Cambridge University Press eBooks. https://doi.org/10.1017/9781108686136

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.