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Associating geo-coordinates with the content of social media posts canenhance many existing applications and services and enable a host of new ones.Unfortunately, a majority of social media posts are not tagged withgeo-coordinates. Even when location data is available, it may be inaccurate,very broad or sometimes fictitious. Contemporary location estimation approachesbased on analyzing the content of these posts can identify only broad areassuch as a city, which limits their usefulness. To address these shortcomings,this paper proposes a methodology to narrowly estimate the geo-coordinates ofsocial media posts with high accuracy. The methodology relies solely on thecontent of these posts and prior knowledge of the wide geographical region fromwhere the posts originate. An ensemble of language models, which are smoothedover non-overlapping sub-regions of a wider region, lie at the heart of themethodology. Experimental evaluation using a corpus of over half a milliontweets from New York City shows that the approach, on an average, estimateslocations of tweets to within just 2.15km of their actual positions.

Accurate Local Estimation of Geo-Coordinates for Social Media Posts