UKTwitNewsCor: A Dataset of Online Local News Articles for the Study of Local News Provision

Authors

  • Simona Bisiani Surrey Institute for People-Centred AI, University of Surrey
  • Agnes Gulyas Canterbury Christ Church University
  • John Wihbey Northeastern University
  • Bahareh Heravi Surrey Institute for People-Centred AI, University of Surrey

DOI:

https://doi.org/10.1609/icwsm.v19i1.35940

Abstract

In this paper, we present UKTwitNewsCor, a comprehensive dataset for understanding the content production, dissemination, and audience engagement dynamics of online local media in the UK. It comprises over 2.5 million online news articles published between January 2020 and December 2022 from 360 local outlets. The corpus represents all articles shared on Twitter by the social media accounts of these outlets. We augment the dataset by incorporating social media performance metrics for the articles at the tweet level. We further augment the dataset by creating metadata about content duplication across domains. Alongside the article dataset, we supply three additional datasets: a directory of local media web domains, one of UK Local Authority Districts, and one of digital local media providers, providing statistics on the coverage scope of UKTwitNewsCor. Our contributions enable comprehensive, longitudinal analysis of UK local media, news trends, and content diversity across multiple platforms and geographic areas. In this paper, we describe the data collection methodology, assess the dataset geographic and media ownership diversity, and outline how researchers, policymakers, and industry stakeholders can leverage UKTwitNewsCor to advance the study of local media.

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Published

2025-06-07

How to Cite

Bisiani, S., Gulyas, A., Wihbey, J., & Heravi, B. (2025). UKTwitNewsCor: A Dataset of Online Local News Articles for the Study of Local News Provision. Proceedings of the International AAAI Conference on Web and Social Media, 19(1), 2371–2384. https://doi.org/10.1609/icwsm.v19i1.35940