Back to Search Start Over

Explain sentiments using Conditional Random Field and a Huge Lexical Network

Authors :
Tapi Nzali, Mike Donald
Maïzi, Joël
Pompidor, Pierre
Bringay, Sandra
Lavergne, Christian
Bascoul-Mollevi, Caroline
ADVanced Analytics for data SciencE (ADVANSE)
Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM)
Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)
Institut Montpelliérain Alexander Grothendieck (IMAG)
Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)
Université de Montpellier (UM)
Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)
Université Paul-Valéry - Montpellier 3 (UPVM)
UNICANCER - Institut régional du Cancer Montpellier Val d'Aurelle (ICM)
CRLCC Val d'Aurelle - Paul Lamarque
Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)
Source :
2nd Annual International Symposium on Information Management and Big Data, SIMBig: Symposium on Information Management and Big Data, SIMBig: Symposium on Information Management and Big Data, Sep 2015, Cusco, Peru
Publication Year :
2015
Publisher :
HAL CCSD, 2015.

Abstract

International audience; In this paper, we focus on a particular task which consists in explaining the source and the target of sentiments expressed in social networks. We propose a method for French, which overcomes a fine syntactic parsing and successfully integrate the Conditional Random Field (CRF) method and a smart exploration of a very large lexical network. Quantitative and qualitative experiments were performed on real dataset to validate this approach.

Subjects

Subjects :
[INFO]Computer Science [cs]

Details

Language :
English
Database :
OpenAIRE
Journal :
2nd Annual International Symposium on Information Management and Big Data, SIMBig: Symposium on Information Management and Big Data, SIMBig: Symposium on Information Management and Big Data, Sep 2015, Cusco, Peru
Accession number :
edsair.dedup.wf.001..d3fef783ee4fc0610d80583134191a33