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A Semi-Automated Directory System for the UK Local News Landscape: Supporting Policy and Research
Preprint   Open access

A Semi-Automated Directory System for the UK Local News Landscape: Supporting Policy and Research

Simona Bisiani, Joe Mitchell, Agnes Gulyas and Bahareh Heravi
SocArXiv
03/12/2024

Abstract

local journalism Behavioral or Social Studies
The UK local news landscape faces significant challenges, with declines in outlets, staffing, and relevance due to market pressures, digital disruption, and media consolidation. This crisis is compounded by the lack of a comprehensive, up-to-date directory of local news outlets, hindering research and policy interventions. Existing directories are often incomplete, outdated, and fail to capture the diversity of the local media landscape. To address this problem, the Public Interest News Foundation (PINF) has developed a semi-automated system that uses open-source intelligence (OSINT) and computational workflows to maintain a comprehensive and current directory of UK local news outlets across print, digital, radio, and television. The system tracks closures, launches, ownership changes, and geographic coverage, flagging notable events for manual review. This combination of computational analysis and human review substantially reduces manual labour while improving data accuracy. Overall, the system offers a model for future initiatives that seek to track the health of local news ecosystems. The paper discusses its implications for media pluralism, policy intervention, and the sustainability of local journalism, alongside directions for future research.
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Preprint (Author's original) Open Access CC BY-NC V4.0
url
https://doi.org/10.31235/osf.io/zsxdgView
Preprint (Author's original) Open CC BY-NC V4.0

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