publications

2026

1. Journalism

   The hollowing out of local newspapers: A longitudinal study of journalistic performance decline and content homogenisation at a major UK publisher

   Simona Bisiani, Agnes Gulyas, Martin Moore, and Bahareh Heravi

   Journalism, Jul 2026

   DOI

2025

1. Report

   UK Local News Report 2025

   Simona Bisiani and Joe Mitchell

   Jul 2025

   London: Public Interest News Foundation

   DOI
2. CHR

   Mapping News Geography: A Computational Framework for Classifying Local Media Through Geographic Coverage Patterns

   Simona Bisiani, Agnes Gulyas, and Bahareh Heravi

   Jul 2025

   Presented at the 2025 CHR Conference, Luxembourg, December 2025.

   Abs DOI Slides

   This study introduces a novel computational framework for defining local news outlets through their geographic coverage patterns. This approach addresses the growing disconnect between legacy spatial markers (e.g., newsroom location or circulation cut-offs) and the geographic dimension of news coverage in an era of media consolidation and digital transformation. We develop a four-step pipeline consisting of data sampling, geoparsing, feature engineering, and clustering analysis. Our approach employs large language models for toponym disambiguation and develops eight spatial metrics across four dimensions: spatial extent, administrative reach, spatial heterogeneity, and distance decay. We test this pipeline on a sample of more than 465,000 articles from 360 UK digital local news outlets. Clustering analysis of more than 1.3 million locations reveals six distinct outlet types—ranging from hyperlocal and metropolitan to national outlets—reflecting different scales and structures of news provision in the UK’s evolving media landscape. The method offers a scalable, open-source approach for mapping local news coverage, with implications for media geography and policy, ownership studies, and the computational humanities.

3. Report

   Challenges and opportunities for UK local media: Insights from academic research

   Simona Bisiani and Agnes Gulyas

   Canterbury Christ Church University., Jul 2025

   Abs DOI

   The local media sector in the UK is navigating a period of substantial change: newsrooms are shrinking (Ponsford, 2024), revenues are plummeting (Lu, 2024), and audiences are disengaging (Newman et al., 2024). Amidst these changes, a long tail of smaller, independent media producers have stepped in to address underrepresented topics, niches, or local areas (Anderson, 2007), however they face significant revenue challenges threatening their long-term sustainability (Cook et al., 2024). Despite its imperfections, local media remains essential to fostering informed and connected communities by providing essential information, shaping public opinion, and preserving local identity (Nielsen, 2015). In this context of disruption and adaptation, evidence-based strategies have never been more necessary. However, we argue that a significant gap exists between the wealth of academic research available and its practical application within the UK local media industry. This report explores the challenges facing UK local media through the lens of academic research, designed to bridge the gap between scholarly inquiry and industry practice. It synthesises insights from a comprehensive literature review of British and international academic sources from the Scopus database to inform media organisations, policymakers, and citizens about the industry’s current state, challenges, and ongoing relevance.

4. CHR

   Towards Efficient and Accessible Geoparsing of UK Local Media: A Benchmark Dataset and LLM-based Approach

   Simona Bisiani, Agnes Gulyas, and Bahareh Heravi

   Computational Humanities Research, Jul 2025

   Special issue: Expanding the Toolkit: Large Language Models in Humanities Research

   Abs DOI Bib

   Location mentions in local news are crucial for examining issues like spatial inequalities, news deserts, and the impact of media ownership on news diversity. However, while geoparsing—extracting and resolving location mentions—has advanced through statistical and deep learning methods, its use in local media studies remains limited and fragmented due to technical challenges and a lack of practical frameworks. To address these challenges, we identify key considerations for successful geoparsing and review spatially oriented local media studies, finding over-reliance on limited geospatial vocabularies, limited toponym disambiguation, and inadequate validation of methods. These findings underscore the need for adaptable and robust solutions, and recent advancements in fine-tuned Large Language Models (LLMs) for geoparsing offer a promising direction by simplifying technical implementation and excelling at understanding contextual nuances. However, their application to UK local media—marked by fine-grained geographies and colloquial place names—remains underexplored due to the absence of benchmark datasets. This gap hinders researchers’ ability to evaluate and refine geoparsing methods for this domain. To address this, we introduce the Local Media UK Geoparsing (LMUK-Geo) dataset, a hand-annotated corpus of UK local news articles designed to support the development and evaluation of geoparsing pipelines. We also propose an LLM-driven approach for toponym disambiguation that replaces fine-tuning with accessible prompt engineering. Using LMUK-Geo, we benchmark our approach against a fine-tuned method. Both perform well on the novel dataset: the fine-tuned model excels in minimising coordinate-error distances, while the prompt-based method offers a scalable alternative for district-level classification, particularly when relying on predictions agreed upon by multiple models. Our contributions establish a foundation for geoparsing local media, advancing methodological frameworks and practical tools to enable systematic and comparative research.

   @article{bisiani_towards_2025,
     title = {Towards Efficient and Accessible Geoparsing of {UK} Local Media: A Benchmark Dataset and {LLM}-based Approach},
     url = {https://doi.org/10.1017/chr.2025.10012},
     doi = {10.1017/chr.2025.10012},
     journal = {Computational Humanities Research},
     author = {Bisiani, Simona and Gulyas, Agnes and Heravi, Bahareh},
     year = {2025},
     note = {Special issue: Expanding the Toolkit: Large Language Models in Humanities Research},
     pages = {1--20}
   }

5. ICWSM

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

   Simona Bisiani, Agnes Gulyas, John Wihbey, and Bahareh Heravi

   Proceedings of the International AAAI Conference on Web and Social Media, Jul 2025

   Abs DOI Bib Poster

   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.

   @article{bisiani_uktwitnewscor_2025,
     title = {{UKTwitNewsCor}: A Dataset of Online Local News Articles for the Study of Local News Provision},
     volume = {19},
     url = {https://ojs.aaai.org/index.php/ICWSM/article/view/35940},
     doi = {10.1609/icwsm.v19i1.35940},
     pages = {2371--2384},
     number = {1},
     journal = {Proceedings of the International {AAAI} Conference on Web and Social Media},
     author = {Bisiani, Simona and Gulyas, Agnes and Wihbey, John and Heravi, Bahareh},
     year = {2025},
   }

6. LJRW

   Computational Tools for Mapping and Measuring Local News Diversity at Scale

   Simona Bisiani

   Local Journalism Researchers WorkshopUNC, North Carolina , Jul 2025

   Abs Slides

   Presentation from the Local News Researchers Workshop (UNC, March 2025) covering large-scale computational approaches to assess diversity in local news content. Includes methodologies for: content syndication detection using Min-Hashing and LSH algorithms; geographic focus analysis through LLM-based geoparsing; and analysis of the UK commercial and independent digital news sector using the UKTwitNewsCor dataset (360 domains, 87 publishers, 2.5M articles). Key findings: 22% content repurposing rate, with syndication occurring primarily at short distances (median 33km) and instantaneously (median 0h delay). Demonstrates scalable computational methods for national-level assessments of local media provision.

2024

1. Report

   UK Local News Report April 2024

   Simona Bisiani and Joe Mitchell

   Jul 2024

   London: Public Interest News Foundation

   DOI
2. Preprint

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

   Simona Bisiani, Joe Mitchell, Agnes Gulyas, and Bahareh Heravi

   Jul 2024

   Abs DOI Bib Poster

   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, the Public Interest News Foundation (PINF) has developed a semi-automated system leveraging open-source intelligence (OSINT) and computational workflows to maintain a comprehensive and current directory of local news outlets across print, digital, radio, and television in the UK. This system tracks closures, launches, ownership changes, and geographic coverage. Notable events are flagged for manual review. This research and review pipeline, combining computational analysis with human review, significantly reduces manual labor while enhancing data accuracy. Overall, the system offers a model for future initiatives aimed at tracking the health of local news ecosystems. The implications of this system for media pluralism, policy interventions, and the sustainability of local journalism are discussed, alongside suggestions for future research.

   @article{bisiani_mitchell_gulyas_heravi_2024,
     title = {A Semi-Automated Directory System for the UK Local News Landscape: Supporting Policy and Research},
     url = {osf.io/preprints/socarxiv/zsxdg},
     doi = {10.31235/osf.io/zsxdg},
     publisher = {SocArXiv},
     author = {Bisiani, Simona and Mitchell, Joe and Gulyas, Agnes and Heravi, Bahareh},
     year = {2024},
   }

2023

1. Journalism and Media

   Uncovering the State of Local News Databases in the UK: Limitations and Impacts on Research

   Simona Bisiani and Bahareh Heravi

   Journalism and Media, Jul 2023

   Abs DOI Bib

   Local journalism is fundamental for a thriving democracy, yet the UK faces a decline in the number of print and digital local news outlets. Large-scale mappings of the surviving outlets offer invaluable insights to policymakers designing interventions to strengthen the sector. Due to the lack of a comprehensive national directory of UK print and digital local news outlets, researchers have resorted to datasets such as circulation auditors’ databases, which have been additional_infod to be incomplete and outdated. A lack of understanding of the magnitude of these data limitations hinders researchers from selecting optimal datasets. This study evaluates four commonly used local news databases, uncovering significant variations in their currentness and comprehensiveness. Thereafter, statistical analyses demonstrate the significant effect of each dataset’s shortcomings on findings in local news research. To address this issue, triangulation and manual verification are employed to create a more comprehensive and robust dataset. This procedure generates a new national dataset of print and digital local news outlets that can be used in future research, alongside a framework for leveraging public data to build an independent research dataset. This work paves the way for more rigorous research in data-driven local news provision studies. Concluding remarks stress the importance of setting definitions and establishing clear data pipelines in an increasingly diversified and dynamic sector.

   @article{bisiani_uncovering_2023,
     title = {Uncovering the State of Local News Databases in the {UK}: Limitations and Impacts on Research},
     volume = {4},
     issn = {2673-5172},
     url = {https://www.mdpi.com/2673-5172/4/4/77},
     doi = {10.3390/journalmedia4040077},
     pages = {1211--1231},
     number = {4},
     journal = {Journalism and Media},
     author = {Bisiani, Simona and Heravi, Bahareh},
     year = {2023}
   }

2. Journalism Practice

   The Data Journalism Workforce: Demographics, Skills, Work Practices, and Challenges in the Aftermath of the COVID-19 Pandemic

   Simona Bisiani, Andrea Abellan, Félix Arias Robles, and José Alberto García-Avilés

   Journalism PracticePublisher: Routledge , Jul 2023

   Abs DOI Bib

   In the last decade, data journalism has established itself as a thriving field. Recently, COVID-19 has boosted the demand for data-driven reporting to make sense of the pandemic, increasing the importance of studying the evolution of this rapidly evolving and technology-bounded practice. However, the number of efforts to map and systematically measure the data journalism industry are few. This paper analyses the findings of The State of the Data Journalism Survey 2021, currently the most extensive study on the characteristics surrounding the workforce producing and contributing to the data journalism industry. The outcome is an understanding of an expanding workforce with a geographically uneven distribution, which is still homogeneous in terms of tools and educational paths. Self-taught, resourceful, and multi-skilled, data journalists often work in isolation but share pressures of limited resources, time limitations, and access to quality data. The pandemic appears to have directly increased those struggles, although data journalists agree that the field’s reputation has ultimately benefited from it.

   @article{bisiani_data_2023,
     title = {The Data Journalism Workforce: Demographics, Skills, Work Practices, and Challenges in the Aftermath of the {COVID}-19 Pandemic},
     volume = {0},
     issn = {1751-2786},
     url = {https://doi.org/10.1080/17512786.2023.2191866},
     doi = {10.1080/17512786.2023.2191866},
     shorttitle = {The Data Journalism Workforce},
     pages = {1--21},
     number = {0},
     journal = {Journalism Practice},
     author = {Bisiani, Simona and Abellan, Andrea and Arias Robles, Félix and García-Avilés, José Alberto},
     urldate = {2023-12-14},
     year = {2023},
     keywords = {survey, {COVID}-19, Data journalism, demographics, skills, tools, work practices},
     file = {Full Text PDF:C\:\\Users\\sb02767\\Zotero\\storage\\XPACBL8N\\Bisiani et al. - 2023 - The Data Journalism Workforce Demographics, Skill.pdf:application/pdf}
   }

3. C+J

   Data Journalism Today: A Comparative Analysis of Two Consecutive Surveys

   Simona Bisiani

   The Joint Computation + Journalism and European Data and Computational Journalism Conference 2023ETH, Zurich , Jul 2023

   Slides