Lexicons for Sentiment, Affect, and Connotation

23.6 Using lexicons for sentiment recognition

1. When are lexicons useful for sentiment classification, and what is the simplest rule-based method?
   When there is not enough labeled training data. Count (optionally weighted) positive and negative lexicon words, \(f^+\) and \(f^-\): classify positive if \(f^+/f^- > \lambda\), negative if \(f^-/f^+ > \lambda\), otherwise neutral.
   • Jurafsky & Martin, Speech and Language Processing, 3rd ed. draft, ch. 23, §23.6, p. 533
2. How are lexicons used when supervised training data is available?
   Lexicon counts (weighted or normalized) become features in a classifier alongside other lexical and non-lexical features.
   • Jurafsky & Martin, Speech and Language Processing, 3rd ed. draft, ch. 23, §23.6, p. 533