Paper: Contextual Phrase-Level Polarity Analysis Using Lexical Affect Scoring and Syntactic N-Grams

ACL ID E09-1004
Title Contextual Phrase-Level Polarity Analysis Using Lexical Affect Scoring and Syntactic N-Grams
Venue Annual Meeting of The European Chapter of The Association of Computational Linguistics
Session Main Conference
Year 2009
Authors

We present a classifier to predict con- textual polarity of subjective phrases in a sentence. Our approach features lexi- cal scoring derived from the Dictionary of Affect in Language (DAL) and extended through WordNet, allowing us to automat- ically score the vast majority of words in our input avoiding the need for manual la- beling. We augment lexical scoring with n-gram analysis to capture the effect of context. We combine DAL scores with syntactic constituents and then extract n- grams of constituents from all sentences. We also use the polarity of all syntactic constituents within the sentence as fea- tures. Our results show significant im- provement over a majority class baseline as well as a more difficult baseline consist- ing of lexical n-grams.