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Poster De Conférence Année : 2013

Using syntactic features and multi-polarity words for sentiment analysis in twitter

Résumé

This paper presents the contribution of our team at task 2 of SemEval 2013: Sentiment Analysis in Twitter. We submitted a constrained run for each of the two subtasks. In the Contextual Polarity Disambiguation subtask, we use a sentiment lexicon approach combined with polarity shift detection and tree kernel based classifiers. In the Message Polarity Classification subtask, we focus on the influence of domain information on sentiment classification.

Domaines

Linguistique
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Dates et versions

hal-02117305 , version 1 (02-05-2019)

Identifiants

  • HAL Id : hal-02117305 , version 1

Citer

Morgane Marchand, Alexandru Lucian Ginsca, Romaric Besançon, Olivier Mesnard. Using syntactic features and multi-polarity words for sentiment analysis in twitter. SEM 2013 : Second Joint Conference on Lexical and Computational Semantics, Jun 2013, Atlanta, United States. pp.418 - 424, 2013. ⟨hal-02117305⟩
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