Analysing domain suitability of a sentiment lexicon by identifying distributionally bipolar words

• Lucie Flekova ^[1] ; Eugen Ruppert ^[1] ; Daniel Preoţiuc-Pietro ^[2]
  1. [1] Technical University of Darmstadt

     Technical University of Darmstadt

     Kreisfreie Stadt Darmstadt, Alemania

     
  2. [2] University of Pennsylvania

     University of Pennsylvania

     City of Philadelphia, Estados Unidos

     
• 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. 77-84
• Idioma: inglés
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• Resumen

  • Contemporary sentiment analysis ap- proaches rely heavily on lexicon based methods. This is mainly due to their simplicity, although the best empirical results can be achieved by more complex techniques. We introduce a method to assess suitability of generic sentiment lexicons for a given domain, namely to identify frequent bigrams where a polar word switches polarity. Our bigrams are scored using Lexicographers Mutual Information and leveraging large automatically obtained corpora. Our score matches human perception of polarity and demonstrates improvements in classification results using our enhanced context- aware method. Our method enhances the assessment of lexicon based sentiment de- tection algorithms and can be further used to quantify ambiguous words.