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

Authors :
Nozza, D
Ristagno, F
Palmonari, M
Fersini, E
Manchanda, P
Messina, V
NOZZA, DEBORA
PALMONARI, MATTEO LUIGI
FERSINI, ELISABETTA
MANCHANDA, PIKAKSHI
MESSINA, VINCENZINA
Nozza, D
Ristagno, F
Palmonari, M
Fersini, E
Manchanda, P
Messina, V
NOZZA, DEBORA
PALMONARI, MATTEO LUIGI
FERSINI, ELISABETTA
MANCHANDA, PIKAKSHI
MESSINA, VINCENZINA
Publication Year :
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.

Details

Database :
OAIster
Notes :
English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1311393664
Document Type :
Electronic Resource