PLN-PUCRS at EmoInt-2017: Psycholinguistic features for emotion intensity prediction in tweets

• Henrique D. P. dos Santos ^[1] ; Renata Vieira ^[1]
  1. [1] Pontifícia Universidade Católica do Rio Grande do Sul

     Pontifícia Universidade Católica do Rio Grande do Sul

     Brasil

     
• 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. 189-192
• Idioma: inglés
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• Resumen

  • Linguistic Inquiry and Word Count (LIWC) is a rich dictionary that map words into several psychological cat- egories such as Affective, Social, Cognitive, Perceptual and Biological processes. In this work, we have used LIWC psycholinguistic categories to train regression models and predict emotion intensity in tweets for the EmoInt-2017 task. Results show that LIWC features may boost emotion intensity prediction on the basis of a low dimension set.