Upcoming
Towards Efficient and Accessible Geoparsing of Local Media: A Benchmark Dataset and LLM-based Approach
Date & Time
01/10/2025 1:15 pm – 2:45 pm
Simona Bisiani
Surrey Institute for People-Centred AI
Simona Bisiani is a Doctoral Researcher at the Surrey Institute for People-Centred Artificial Intelligence. Her PhD focuses on measuring spatial variations in news coverage in the UK, in order to understand the robustness of local media coverage across the country, how ownership consolidation affects media diversity and relevance, and how media diversity and relevance in turn affect democratic engagement. Her primary research methods are text mining through Natural Language Processing and statistical inference. She holds a MSc in Computational Social Science.
About the Event
This seminar introduces an innovative computational framework for extracting geographic references in local news, leveraging open-source, locally-run large language models. The first segment details the methodology, highlights its advantages over traditional approaches, and illustrates its application in identifying spatial patterns in news coverage—shedding light on media deserts and information inequalities across communities. A code demonstration will showcase the implementation using LMUK-Geo, a newly developed annotated corpus of UK local news articles designed for geoparsing evaluation. Attendees will leave with actionable knowledge to integrate these tools and methods into their research on local media landscapes and geographic trends.
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