Towards geo-referencing infrastructure for local news

Local news articles are an important source of knowledge about local events, place-specific culture, and peoples' thoughts about their environment. Reliable geocoding of such articles is the first step towards unlocking such local knowledge for community engagement and development. However, existing geo-referencing methods and tools do not work well for local news because they do not reflect the ways local people encode and communicate geographical knowledge. This paper argues that local news requires a different method and infrastructure support for effective geo-referencing. To gain insights on the unique aspects of local gazetteers and the nature of ambiguities, we present an analysis of a collection of local new articles. We found that place references in local news have their special vocabulary, and that their ambiguities are handled differently by local people. We translated such insights into a gazetteer-based geocoding solution that combines progressive geocoding with a smart footprint recommender. Progressive geocoding service uses Nominatim (OpenStreetMap) as the initial gazetteer to jump-start the construction of local gazetteer for a community and by the community. LocusRecommender automatically suggests the best matches from gazetteer ranked by a set of heuristic rules. Preliminary evaluation shows that our smart footprint recommender predicts 80% of the answers by its top-three recommendations.