Explain sentiments using Conditional Random Field and a Huge Lexical Network

Abstract : 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.
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Communication dans un congrès
SIMBig: Symposium on Information Management and Big Data, Sep 2015, Cusco, Peru. 2nd Annual International Symposium on Information Management and Big Data, CEUR Workshop Proceedings (1478), 2015, Information Management and Big Data. 〈http://simbig.org/SIMBig2015/〉
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Contributeur : Mike Donald Tapi Nzali <>
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Mike Donald Tapi Nzali, Joël Maïzi, Pierre Pompidor, Sandra Bringay, Christian Lavergne, et al.. Explain sentiments using Conditional Random Field and a Huge Lexical Network. SIMBig: Symposium on Information Management and Big Data, Sep 2015, Cusco, Peru. 2nd Annual International Symposium on Information Management and Big Data, CEUR Workshop Proceedings (1478), 2015, Information Management and Big Data. 〈http://simbig.org/SIMBig2015/〉. 〈hal-01222611〉

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