LIPN-UAM at EmoInt-2017: Combination of Lexicon-based features and Sentence-level Vector Representations for Emotion Intensity Determination

• Davide Buscaldi ^[1] ; Belem Priego ^[2]
  1. [1] Paris 13 University

     Paris 13 University

     Arrondissement de Saint-Denis, Francia

     
  2. [2] UAM Atzcapotzalco, Mexico
• Localización: 8th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis WASSA 2017: Proceedings of the Workshop / Alexandra Balahur Dobrescu (ed. lit.), Saif M. Mohammad (ed. lit.), Erik van der Goot (ed. lit.), 2017, ISBN 978-1-945626-95-1, págs. 255-258
• Idioma: inglés
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• Resumen

  • This paper presents the combined LIPN- UAM participation in the WASSA 2017 Shared Task on Emotion Intensity. In particular, the paper provides some high- lights on the system that was presented to the shared task, partly based on the Tweetaneuse system used to participate in a French Sentiment Analysis task (DEFT2017). We combined lexicon-based features with sentence-level vector rep- resentations to obtain a random forest model.