Using Combined Lexical Resources to Identify Hashtag Types

• Credell Simeon ^[1] ; Robert Hilderman ^[1]
  1. [1] University of Regina

     University of Regina

     Canadá

     
• Localización: 6th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis WASSA 2015: Workshop Proceedings : 17 September 2015 Lisboa, Portugal / Alexandra Balahur Dobrescu (ed. lit.), Erik van der Goot (ed. lit.), Piek Vossen (ed. lit.), Andrés Montoyo Guijarro (ed. lit.), 2015, ISBN 978-1-941643-32-7, págs. 169-174
• Idioma: inglés
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• Resumen

  • This paper seeks to identify sentiment and non-sentiment bearing hashtags by com- bining existing lexical resources. By using a lexicon-based approach, we achieve 86.3% and 94.5% precision in identifying sentiment and non-sentiment hashtags, respectively. Moreover, results obtained from both of our classification models demonstrate that using combined lexical, emotion and word resources is more effective than using a single resource in identifying the two types of hashtags.