. Author manuscript; available in PMC: 2017 Feb 21.

Published in final edited form as: Proc ACM Int Conf Inf Knowl Manag. 2016 Oct;2016:939–948. doi: 10.1145/2983323.2983793

Table 2.

Comparison of classification accuracy (%).

	Algo. & Features	RT	Yelp	IMDB

unigram	Linear SVM	76.2 ^*	91.87	87.8 ^†
	Logistic	76.9	91.90	88.19
	NBSVM	78.1 ^*	92.13	88.29 ^*
	MTSA	78.0	92.20	88.57
	MTSA(fixed negation)	78.3	92.20	88.48
	MTSA(NB)	78.3	92.52	88.81
	MTSA(shifter)	78.4	92.78	88.82
	MTSA(NB + shifter)	78.8	93.08	88.97

bigram	Linear SVM	77.7 ^*	91.93	89.16 ^*
	Logistic	78.1	92.99	89.18
	NBSVM	79.4 ^*	93.99	91.22 ^*
	MTSA(NB + shifter)^‡	81.3	94.07	90.44

^†

reported in [18]; binary features with cosine normalization (bnc).

reported in [35]; NBSVM is an ensemble method.

^‡

The top bigram features from Logistic bigram are appended to feature vectors.