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Local News in National Elections

An “Audit” Approach to Assessing Local News Performance During a National Election Campaign

Bibliographic Data

ID22010889
AuthorsMartin Moore (0000-0002-6708-1330, King's College London, corresponding author), Gordon Neil Ramsay (0000-0002-2429-0925, University of Akureyri)
Year2025
Volume13
Issue10
Pages1796-1815
Publication date2025-11-26
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueDigital Journalism (JOURNAL)
Journal identifiersISSN: 2167-0811 • E-ISSN: 2167-082X
PublisherInforma UK Limited (PUBLISHER • GB)
DOI10.1080/21670811.2024.2333827
OpenAlexW4393261332
LanguageEN
References cited31

As local news organizations struggle to adapt to new economic realities while suffering structural disadvantages in an engagement-driven online media environment, there is a critical need for empirical data to assess how well local news media continue to serve different communities to inform forthcoming state and non-state interventions to safeguard the delivery of public interest journalism. This paper presents the findings of a project that makes three contributions to the field of local news performance analysis. First, it tests the effectiveness of an open-source news analysis toolkit, Steno, on a large sample of over 70,000 online local news articles. Second, it applies an established framework for news analysis at the local level and adapts it to analyse local news outlets across an entire country. Third, it generates the first ever “audit” of local news performance during a national election campaign. The purpose of the paper is therefore to establish empirical benchmarks for future analysis and policy interventions in one country (the United Kingdom), and to test methodological techniques that may be replicated in other media systems

Advertising · Audit · Business · National election · News media · Political science · Politics · Public relations · Law · Media Influence and Politics · Media Studies and Communication · Public Administration · Social Media and Politics · Accounting

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