Serving the public interest? A computational analysis of the topics of UK national newspaper coverage using Freedom of Information (FOI) requests between 2005 and 2023

Tong, J. orcid.org/0000-0001-6843-3177 (2025) Serving the public interest? A computational analysis of the topics of UK national newspaper coverage using Freedom of Information (FOI) requests between 2005 and 2023. Journalism Studies. ISSN 1461-670X

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Item Type: Article
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© 2025 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.

Keywords: Freedom of information; Latent Dirichlet allocation (LDA) topic modelling; n-gram analysis; machine learning; computational social science; political communication; journalism; The UK
Dates:
  • Accepted: 2 June 2025
  • Published (online): 6 July 2025
  • Published: 6 July 2025
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Social Sciences (Sheffield) > Department of Journalism Studies (Sheffield)
Funding Information:
Funder
Grant number
BRITISH ACADEMY (THE)
SRG21\211038
Depositing User: Symplectic Sheffield
Date Deposited: 14 Jul 2025 10:41
Last Modified: 17 Jul 2025 08:41
Published Version: https://doi.org/10.1080/1461670x.2025.2518453
Status: Published online
Publisher: Taylor & Francis
Refereed: Yes
Identification Number: 10.1080/1461670x.2025.2518453
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Sustainable Development Goals:
  • Sustainable Development Goals: Goal 16: Peace, Justice, and Strong Insitutions
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