  More and more of the information on the web is dialogic, from Facebook
newsfeeds, to forum conversations, to comment threads on news articles. In
contrast to traditional, monologic resources such as news, highly social
dialogue is very frequent in social media. We aim to automatically identify
sarcastic and nasty utterances in unannotated online dialogue, extending a
bootstrapping method previously applied to the classification of monologic
subjective sentences in Riloff and Weibe 2003. We have adapted the method to
fit the sarcastic and nasty dialogic domain. Our method is as follows: 1)
Explore methods for identifying sarcastic and nasty cue words and phrases in
dialogues; 2) Use the learned cues to train a sarcastic (nasty) Cue-Based
Classifier; 3) Learn general syntactic extraction patterns from the sarcastic
(nasty) utterances and define fine-tuned sarcastic patterns to create a
Pattern-Based Classifier; 4) Combine both Cue-Based and fine-tuned
Pattern-Based Classifiers to maximize precision at the expense of recall and
test on unannotated utterances.
