Geotagging twitter messages in crisis management

Abstract

During times of crisis microblogging platforms such as Twitter have played an important role as a communication channel to distribute information. Particularly, disaster-related tweets are valuable resources when tagged with their location for detecting unexpected events. However, they often contain different types of location and one of the main challenges is resolving the ambiguity involved in their locations. The process of identifying phrase portions in unstructured texts with possible spatial aspects and disambiguating these references by linking them to geographic coordinates is known as Geotagging. In the context of crisis management, this paper presents OzCT geotagger that automatically detects the location(s) mentioned in the content of tweets with three possibilities: definite, ambiguous and no-location. It also semantically annotates the tweet components utilizing existing and new ontologies. The OzCT geotagger has been recently deployed in a trial system of the OzCrisisTracker application. Experiments demonstrate that the precision and recall for detection of the definite locations against geotagging by human judgement are on average of 80%. We also conclude that the accuracy of geographical focus of the OzCT geotagger is considerably higher than other systems. While existing geocoding systems have lower coverage for suburb and street focus, our approach detects suburbs in more than 60% situations.