TweeLoc: A System for Geolocalizing Tweets at Fine-Grain

The recent rise in the use of social networks has resulted in an abundance of information on different aspects of everyday social activities that is available online. In the process of analysis of identifying the information originating from social networks, and especially Twitter, an important aspect is that of the geographic coordinates, i.e., geolocalisation, of the relevant information. Geolocalized information can be used by a variety of applications in order to offer better, or new services. However, only a small percentage of the twitter posts are geotagged, which restricts the applicability of location-based applications. In this work, we describe TweeLoc, our prototype system for geolocalizing tweets that are not geotagged, which can effectively estimate the tweet location at the level of a city neighborhood. TweeLoc employs a dashboard that visualizes the social activity of the geographic regions specified by the user, and provides relevant easy-to-access statistics. Moreover, it displays information on the way that these statistics evolve over time. Our system can help end-users and large-scale event organizers to better plan and manage their activities, and can complete this task fast and more accurately than alternative solutions that we compare to.