Mapping Great Britain's semantic footprints through a large language model analysis of Reddit comments

Observed regional variation in geotagged social media text is often attributed to dialects, where features in language are assumed to exhibit region-specific properties. While dialects are seen as a key component in defining the identity of regions, there are a multitude of other geographic properties that may be captured within natural language text. In our work, we consider locational mentions that are directly embedded within comments on the social media website Reddit, providing a range of associated semantic information, and enabling deeper representations between locations to be captured. Using a large corpus of geoparsed Reddit comments from UK-related local discussion subreddits, we first extract embedded semantic information using a large language model, aggregated into local authority districts, representing the semantic footprint of these regions. These footprints broadly exhibit spatial autocorrelation, with clusters that conform with the national borders of Wales and Scotland. London, Wales, and Scotland also demonstrate notably different semantic footprints compared with the rest of Great Britain. • Large language models can be leveraged to extract vernacular knowledge of places • Vernacular knowledge of places derived from text-based data is introduced in the form of semantic footprints • Semantic footprints exhibit geographically cohesive patterns; correlating broadly with national boundaries of Great Britain • London, Wales, and Scotland emerge as the most distinct semantic spatial clusters