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Table 11 Performance comparison with other methods

From: SentiHealth: creating health-related sentiment lexicon using hybrid approach

Work Dataset Noise Reduction Features Approach Precision Recall F-measure
Goeuriot et al. (2012) 25,000 reviews Filtering Unigram and bigram Hybrid (lexicon-based + information gain) 0.76 0.52 0.62
Asghar et al. (2015) 15,000 reviews Filtering, tokenization, stop word removal, stemming Unigram, bigram and trigram Supervised (revised mutual information) 0.78 0.64 0.64
Demiroz et al.(2012) 9000 reviews Filtering, stop word removal Bag of words Supervised (delta scoring) 0.75 0.48 0.58
Our work 26,060 reviews Filtering, tokenization, stop word removal, lemmatization, spell correction, co-reference resolution Unigram, bigram and trigram Hybrid (boot strapping + corpus-based) 0.89 0.79 0.83
  1. All the mentioned evaluations measures are as reported by their respective work