@inproceedings{402d12db88324c3c857fefc65cb85f67,
title = "Contextual phrase-level polarity analysis using lexical affect scoring and syntactic N-grams",
abstract = "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 n-grams 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.",
author = "Apoorv Agarwal and Fadi Biadsy and McKeown, \{Kathleen R.\}",
year = "2009",
month = jan,
day = "1",
doi = "10.3115/1609067.1609069",
language = "English",
isbn = "9781932432169",
series = "EACL 2009 - 12th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings",
publisher = "Association for Computational Linguistics (ACL)",
pages = "24--32",
booktitle = "EACL 2009 - 12th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings",
address = "United States",
note = "12th Conference of the European Chapter of the Association for Computational Linguistics , EACL 2009 Student Research Workshop ; Conference date: 30-03-2009 Through 03-04-2009",
}