Paper: An Empirical Study on the Effect of Negation Words on Sentiment

ACL ID P14-1029
Title An Empirical Study on the Effect of Negation Words on Sentiment
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2014
Authors

Negation words, such as no and not, play a fundamental role in modifying sentiment of textual expressions. We will refer to a negation word as the negator and the text span within the scope of the negator as the argument. Commonly used heuristics to estimate the sentiment of negated expres- sions rely simply on the sentiment of ar- gument (and not on the negator or the ar- gument itself). We use a sentiment tree- bank to show that these existing heuristics are poor estimators of sentiment. We then modify these heuristics to be dependent on the negators and show that this improves prediction. Next, we evaluate a recently proposed composition model (Socher et al., 2013) that relies on both the negator and the argument. This model learns the syntax and semantics of the negator?s ar- gument wi...