Istituto di Scienza e Tecnologie dell'Informazione     
Al Emadi N., Abbar S., Borge-Holthoefer J., Guzman F., Sebastiani F. QT2S: a system for monitoring road traffic via fine grounding of tweets. In: ICWSM 2017 - 11th AAAI International Conference on Web and Social Media (Montreal, CA, 15-18 May 2017). Proceedings, pp. 456 - 459. AAAI Press, 2017.
Social media platforms provide continuous access to user generated content that enables real-time monitoring of user behavior and of events. The geographical dimension of such user behavior and events has recently caught a lot of attention in several domains: mobility, humanitarian, or infrastructural. While resolving the location of a user can be straightforward, depending on the affordances of their device and/or of the application they are using, in most cases, locating a user demands a larger effort, such as exploiting textual features. On Twitter for instance, only 2% of all tweets are geo-referenced. In this paper, we present a system for zoomed-in grounding (below city level) for short messages (e.g., tweets). The system combines different natural language processing and machine learning techniques to increase the number of geo-grounded tweets, which is essential to many applications such as disaster response and real-time traffic monitoring.
Subject Tweet grounding
I.2.1 ARTIFICIAL INTELLIGENCE. Applications and Expert Systems. Cartography

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