Transcription of Sentiment Analysis of Twitter Data - Columbia University
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Sentiment Analysis of Twitter Data - Columbia University
Sentiment Analysis of Twitter DataApoorv Agarwal Boyi Xie Ilia Vovsha Owen Rambow Rebecca PassonneauDepartment of Computer ScienceColumbia UniversityNew York, NY 10027 USA{apoorv@cs, xie@cs, iv2121@, rambow@ccls, examine Sentiment Analysis on Twitterdata. The contributions of this paper are: (1)We introduce POS-specific prior polarity fea-tures. (2) We explore the use of a tree kernel toobviate the need for tedious feature engineer-ing. The new features (in conjunction withpreviously proposed features) and the tree ker-nel perform approximately at the same level,both outperforming the state-of-the-art IntroductionMicroblogging websites have evolved to become asource of varied kind of information. This is due tonature of microblogs on which people post real timemessages about their opinions on a variety of topics,discuss current issues, complain, and express posi-tive Sentiment for products they use in daily life. Infact, companies manufacturing such products havestarted to poll these microblogs to get a sense of gen-eral Sentiment for their product.}
Sentiment analysis has been handled as a Natural Language Processing task at many levels of gran-ularity. Starting from being a document level classi-fication task (Turney, 2002; Pang and Lee, 2004), it has been handled at the sentence level (Hu and Liu, 2004; Kim and Hovy, 2004) and more recently at
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