We collect substring rationales for a sentiment classification task ( Pang and Lee , 2004 ) and use them to obtain significant accuracy improvements for each annotator .
a sentimental education sentiment analysis using subjectivity summarization based on minimum cuts
B Pang L Lee
Thus , observing the rationales helps us infer the true 0 . We collect substring rationales for a sentiment classification task ( Pang and Lee , 2004 ) and use them to obtain significant accuracy improvements for each annotator . Our new generative approach exploits the rationales more effectively than our previous `` masking SVM '' approach .
We collect substring rationales for a sentiment classification task ( @@CITATION ) and use them to obtain significant accuracy improvements for each annotator .