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Mining large corpora for social information: The case of elderly

MAUTNER, GERLINDE·2007·Language in Society

Abstract

Using a large, computerized corpus, this study aims to provide lexico-grammatical evidence of stereotypical constructions of age and aging. It focuses on elderly, a word that is pivotal to the domain in question and whose associative meaning is contested. The collocational profile drawn up on the basis of corpus evidence shows that elderly is primarily associated with discourses of care, disability, and vulnerability, emerging less as a marker of chronological age than of perceived social consequences. In addition to making a contribution to discourse-oriented aging research, the article also demonstrates the use of corpus linguistic methods within a sociolinguistic framework.I am grateful to several colleagues for their comments on a draft version, including most notably Susan Hunston, Virpi Ylänne-McEwen, Kieran O'Halloran, Angie Williams, and two anonymous reviewers. Veronika Koller contributed to the initial corpus searches and also provided useful feedback on the first draft. Eva Kerbler's support during the revision phase was invaluable and much appreciated. I am indebted to Wirtschaftsuniversität Wien and the Austrian National Bank (OeNB) for financial support while spending a sabbatical at the Centre for Language and Communication Research of Cardiff University. Material from the Bank of English® reproduced with the kind permission of HarperCollins Publishers Ltd.

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Metadata

Authors
MAUTNER, G.
Venue
Language in Society
Published
2007-01
Volume
36
Issue
1
Pages
51-72
ISSN
  • 0047-4045 (ISSN-L)
  • 1469-8013
OpenAlex
W2043531381
Cited by
183
References
2
FWCI
119.02
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Mining large corpora for social information: The case of elderly. https://app.cochat.ai/papers/10.1017/s0047404507070030
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MAUTNER, G. (2007). Mining large corpora for social information: The case of elderly. Language in Society. https://doi.org/10.1017/s0047404507070030

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