Abstract:Geotagged Social Media (GTSM) data, especially geotagged tweets are valuable sources of information for many important applications. Only small portions of geotagged tweets are available (less than 3%). Identifying tweet location is a challenging problem that has attracted the interest of both academic and industry fields. Existing approaches have satisfactory accuracy at country and city level, but fail in locating more precisely the tweets. This paper presents 𝐹 𝐿𝐴𝐼𝑅, an approach for geolocating tweets … Show more
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