Paper: Columbia NLP: Sentiment Detection of Sentences and Subjective Phrases in Social Media

ACL ID S14-2031
Title Columbia NLP: Sentiment Detection of Sentences and Subjective Phrases in Social Media
Venue Joint Conference on Lexical and Computational Semantics
Session
Year 2014
Authors

We present two supervised sentiment de- tection systems which were used to com- pete in SemEval-2014 Task 9: Senti- ment Analysis in Twitter. The first sys- tem (Rosenthal and McKeown, 2013) clas- sifies the polarity of subjective phrases as positive, negative, or neutral. It is tai- lored towards online genres, specifically Twitter, through the inclusion of dictionar- ies developed to capture vocabulary used in online conversations (e.g., slang and emoticons) as well as stylistic features common to social media. The second sys- tem (Agarwal et al., 2011) classifies entire tweets as positive, negative, or neutral. It too includes dictionaries and stylistic fea- tures developed for social media, several of which are distinctive from those in the first system. We use both systems to par- tic...