In the recent years, the amount of user generated contents shared on the Web has significantly increased, especially in social media environment, e.g. Twitter, Facebook, Google+. This large quantity of data has generated the need of reactive and sophisticated systems for capturing and understanding the underlying information enclosed in them. In this paper we present TWINE, a real-time system for the big data analysis and exploration of information extracted from Twitter streams. The proposed system based on a Named Entity Recognition and Linking pipeline and a multi-dimensional spatial geo-localization is managed by a scalable and flexible architecture for an interactive visualization of micropost streams insights. The demo is available at http://twinemind. cloudapp.net/streaming1,2.
Nozza, D., Ristagno, F., Palmonari, M., Fersini, E., Manchanda, P., Messina, V. (2017). TWINE: A real-time system for TWeet analysis via INformation extraction. In 15th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2017 - Proceedings of the Software Demonstrations (pp.25-28). Association for Computational Linguistics (ACL) [10.18653/v1/e17-3007].
TWINE: A real-time system for TWeet analysis via INformation extraction
NOZZA, DEBORA;PALMONARI, MATTEO LUIGI;FERSINI, ELISABETTA;MANCHANDA, PIKAKSHI;MESSINA, VINCENZINA
2017
Abstract
In the recent years, the amount of user generated contents shared on the Web has significantly increased, especially in social media environment, e.g. Twitter, Facebook, Google+. This large quantity of data has generated the need of reactive and sophisticated systems for capturing and understanding the underlying information enclosed in them. In this paper we present TWINE, a real-time system for the big data analysis and exploration of information extracted from Twitter streams. The proposed system based on a Named Entity Recognition and Linking pipeline and a multi-dimensional spatial geo-localization is managed by a scalable and flexible architecture for an interactive visualization of micropost streams insights. The demo is available at http://twinemind. cloudapp.net/streaming1,2.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.