TWINE: A real-time system for TWeet analysis via INformation Extraction

Debora Nozza, Fausto Ristagno, Matteo Palmonari, Elisabetta Fersini, Pikakshi Manchanda, Enza Messina


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://twine-mind.cloudapp.net/streaming.
Anthology ID:
E17-3007
Volume:
Proceedings of the Software Demonstrations of the 15th Conference of the European Chapter of the Association for Computational Linguistics
Month:
April
Year:
2017
Address:
Valencia, Spain
Editors:
André Martins, Anselmo Peñas
Venue:
EACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
25–28
Language:
URL:
https://aclanthology.org/E17-3007
DOI:
Bibkey:
Cite (ACL):
Debora Nozza, Fausto Ristagno, Matteo Palmonari, Elisabetta Fersini, Pikakshi Manchanda, and Enza Messina. 2017. TWINE: A real-time system for TWeet analysis via INformation Extraction. In Proceedings of the Software Demonstrations of the 15th Conference of the European Chapter of the Association for Computational Linguistics, pages 25–28, Valencia, Spain. Association for Computational Linguistics.
Cite (Informal):
TWINE: A real-time system for TWeet analysis via INformation Extraction (Nozza et al., EACL 2017)
Copy Citation:
PDF:
https://aclanthology.org/E17-3007.pdf
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