Transcription of Sentiment Analysis of Twitter Data - Columbia University
{{id}} {{{paragraph}}}
Example: dental hygienist
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.}
A man-ual analysis of a random sample of tweets labeled as “junk” suggested that many of these tweets were those that were not translated well using Google translate. We eliminate the tweets with junk la-bel for experiments. This leaves us with an unbal-anced sample of 8,753 tweets. We use stratified sam-
Tags:
Information
Domain:
Source:
Link to this page:
Please notify us if you found a problem with this document: