Evolution and Evaluation: Sarcasm Analysis for Twitter Data Using Sentiment Analysis

Table 2

Comparison with other work.

Authors	Sarcasm dataset	Classifiers used							Accuracy gained
		LR	SVM	RF	KNN	DT	NB	AB
[8]	Twitter								DT: 71.05; NB: 75.18; RF: 77.94; AB: 76.06; LR: 32.03
[13]	Twitter: general election								SVM: 80
[19]	Twitter								NB: 57; LR: 80; RF: 80.5
[12]	Facebook								NB: 73.66; SVM: 88.3
[1]	Twitter								SVM: 79; LR: 80
[20]	Twitter								SVM: 77.9; KNN: 58; RF: 81

LR: Logistic regression, SVM: Support vector machine, RF: Random forest, KNN: K-nearest neighbor, DT: Decision tree, NB: Naïve Bayes, AB: AdaBoost.