We use the same set of binary features as in previous work on this dataset ( Pang et al. , 2002 ; Pang and Lee , 2004 ; Zaidan et al. , 2007 ) .
thumbs up sentiment classification using machine learning techniques
B Pang L Lee S Vaithyanathan
where ~ f ( Â· ) extracts a feature vector from a classified ~ document , Î¸ are the corresponding weights of those features , and ZÎ¸ ( x ) def Ey u ( x , y ) is a normalizer . We use the same set of binary features as in previous work on this dataset ( Pang et al. , 2002 ; Pang and Lee , 2004 ; Zaidan et al. , 2007 ) . Specifically , let V = -LCB- v1 , ... , v177441 be the set of word types with count > 4 in the full 2000-document corpus .
We use the same set of binary features as in previous work on this dataset ( @@CITATION ; Pang and Lee , 2004 ; Zaidan et al. , 2007 ) .