On-line Geospatial Term Extraction from Streaming Geotagged Tweets
Recently, geotagged posts to social media such as Twitter have become major sources for geospatial information referenced to a set of geographic coordinates. Especially, many existing work collects geospatial terms which identify geographic locations by examining the spatial locality of the term usage patterns observed in the geotagged posts accumulated for a certain period of time. Although the spatial locality of the collected geospatial terms can only be temporary, such time variability difference among the geospatial terms have not been considered in the existing work. Thus, in order to separately collect the stationary and temporary geospatial terms with proper timing, we propose an on-line method for constructing a geographical dictionary containing the up-to-date geospatial terms and their locations by continuously examining the spatial locality of terms in streaming geotagged posts. The geospatial terms can be distinguished between stationary and temporary terms according to their usage patterns in the recent set of geotagged posts and their locations recorded in the geographical dictionary. Additionally, images representing each geospatial term can also be collected from the posts containing the corresponding term. The usefulness of the collected geospatial information is demonstrated in comparison to existing geographical dictionaries constructed by experts, crowdsourcing, and batch method.