Dynamic sentiment ambiguous adjectives (DSAAs) like " large, small, high, low" pose a challenging task on sentiment analysis. This paper proposes a knowledge-based method to automatically determine the semantic orientation of DSAAs within context. The task is reduced to sentiment classification of target nouns, which we refer to sentiment expectation instead of semantic orientation widely used in previous researches. We mine the Web using lexico-syntactic patterns to infer sentiment expectation of nouns, and then exploit character-sentiment model to reduce noises caused by the Web data. At sentence level, our method achieves promising result with an f-score of 78.52% that is substantially better than baselines. At document level, our method outperforms previous work in sentiment classification of product reviews.
REF try to infer the polarity of ambiguous adjectives.
Disambiguating Dynamic Sentiment Ambiguous Adjectives
COLING
Computer Science