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.
CITATION STYLE
Nozza, D., Ristagno, F., Palmonari, M., Fersini, E., Manchanda, P., & Messina, E. (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). https://doi.org/10.18653/v1/e17-3007
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