Skip navigation
Logo
User training | Reference and search service

Library catalog

Retrievo
EDS
b-on
More
resources
Content aggregators
Please use this identifier to cite or link to this item:

acessibilidade

http://hdl.handle.net/10071/16047
acessibilidade
Title: Detecting relevant tweets in very large tweet collections: the London Riots case study
Authors: Carvalho, J. P.
Rosa, H.
Batista, F.
Keywords: Twitter
Fingerprint recognition
Market research
Tagging
Libraries
Electronic mail
Databases
Issue Date: 2017
Publisher: IEEE
Abstract: In this paper we propose to approach the subject of detecting relevant tweets when in the presence of very large tweet collections containing a large number of different trending topics. We use a large database of tweets collected during the 2011 London Riots as a case study to demonstrate the application of the proposed techniques. In order to extract relevant content, we extend, formalize and apply a recent technique, called Twitter Topic Fuzzy Fingerprints, which, in the scope of social media, outperforms other well known text based classification methods, while being less computationally demanding, an essential feature when processing large volumes of streaming data. Using this technique we were able to detect 45% additional relevant tweets within the database.
Peer reviewed: yes
URI: https://ciencia.iscte-iul.pt/id/ci-pub-38411
http://hdl.handle.net/10071/16047
DOI: 10.1109/FUZZ-IEEE.2017.8015635
ISBN: 978-1-5090-6034-4
ISSN: 1098-7584
Appears in Collections:CTI-CRI - Comunicações a conferências internacionais

Files in This Item:
acessibilidade
File Description SizeFormat 
Carvalho 2017a - Detecting relevant tweets in very large tweet collections the London Riots case study.pdfPós-print275.51 kBAdobe PDFView/Open


FacebookTwitterDeliciousLinkedInDiggGoogle BookmarksMySpace
Formato BibTex MendeleyEndnote Currículo DeGóis 

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.