Grieve, J., Montgomery, C. orcid.org/0000-0002-3017-2909, Nini, A. et al. (2 more authors) (2019) Mapping lexical dialect variation in British English using Twitter. Frontiers in Artificial Intelligence, 2. 11. ISSN 2624-8212
Abstract
There is a growing trend in sociolinguistics and dialectology to analyse large corpora of social media data, but it is unclear if the results of these studies can be generalised to language as a whole. To assess the generalisability of Twitter dialect maps, this paper presents the first systematic comparison regional lexical variation in Twitter corpora and traditional survey data. We compare the regional patterns found in 139 lexical dialect maps based on a 1.8 billion word corpus of geolocated UK Twitter data and the BBC Voices dialect survey. A spatial analysis of these 139 map pairs finds a strong alignment between these two data sources, offering evidence that both approaches to data collection allow for the same basic underlying regional patterns to be identified. We conclude that these results license the use of Twitter corpora for general inquiries into regional linguistic variation and change.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2019 The Authors. This is an openaccess article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
Keywords: | Social Media; Twitter; British English; dialectology; big data; Lexical variation; spatial analysis; sociolinguistics |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Arts and Humanities (Sheffield) > School of English (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 05 Jul 2019 15:17 |
Last Modified: | 27 Jan 2020 10:48 |
Status: | Published |
Publisher: | Frontiers |
Refereed: | Yes |
Identification Number: | 10.3389/frai.2019.00011 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:148214 |