Your Sentiment Precedes You: Using an author’s historical tweets to predict sarcasm

• Anupam Khattri ^[2] ; Aditya Joshi ^[3] ; Pushpak Bhattacharyya ^[3] ; Mark James Carman ^[1]
  1. [1] Monash University

     Monash University

     Australia

     
  2. [2] IIT Kharagpur, India
  3. [3] IIT Bombay, India

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• 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. 25-30
• Idioma: inglés
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• Resumen

  • Sarcasm understanding may require information beyond the text itself, as in the case of ‘I absolutely love this restaurant!’ which may be sarcastic, depending on the contextual situation. We present the first quantitative evidence to show that historical tweets by an author can provide additional context for sarcasm detection. Our sarcasm detection approach uses two components: a contrast-based predictor (that identifies if there is a sentiment contrast within a target tweet), and a historical tweet-based predictor (that identifies if the sentiment expressed towards an entity in the target tweet agrees with sentiment expressed by the author towards that entity in the past).