Abstract
In the era of smart city, social media platform like twitter has become the most powerful medium for sharing urban issues. Extracting the locations from the complaint tweets is very much helpful to local government for monitoring and performing spatial analysis of civic issues at city level. We propose a natural language processing and regular expression based system to identify probable locations of complaints in terms of landmarks (hospital, mall, railway station), street level (e.g. road marg), region (e.g. nagar, colony) and suburb. Our system has used n-gram matching, string similarity and spatial proximity measures to confirm and disambiguate the extracted locations using GeoNames and OSM gazetteer data. Proposed system has achieved the F-score of 93% which is very promising. Locations are also displayed on map for better situational awareness across the city.
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