期刊名称：Conference on European Chapter of the Association for Computational Linguistics (EACL)
出版年度：2009
卷号：2009
出版社：ACL Anthology
摘要：We present a classifier to predict contextual
polarity of subjective phrases in
a sentence. Our approach features lexical
scoring derived from the Dictionary of
Affect in Language (DAL) and extended
through WordNet, allowing us to automatically
score the vast majority of words in
our input avoiding the need for manual labeling.
We augment lexical scoring with
n-gram analysis to capture the effect of
context. We combine DAL scores with
syntactic constituents and then extract ngrams
of constituents from all sentences.
We also use the polarity of all syntactic
constituents within the sentence as features.
Our results show significant improvement
over a majority class baseline
as well as a more difficult baseline consisting
of lexical n-grams.
