Sentiment analysis of Twitter data

Authors:
Apoorv Agarwal;Boyi Xie;Ilia Vovsha;Owen Rambow;Rebecca Passonneau
Affiliations:
Columbia University, New York, NY;Columbia University, New York, NY;Columbia University, New York, NY;Columbia University, New York, NY;Columbia University, New York, NY
Venue:
LSM '11 Proceedings of the Workshop on Languages in Social Media
Year:
2011

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Abstract

We examine sentiment analysis on Twitter data. The contributions of this paper are: (1) We introduce POS-specific prior polarity features. (2) We explore the use of a tree kernel to obviate the need for tedious feature engineering. The new features (in conjunction with previously proposed features) and the tree kernel perform approximately at the same level, both outperforming the state-of-the-art baseline.