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. 2016 Nov 29;2016:2093406. doi: 10.1155/2016/2093406

Table 5.

Sentiment classification based on different lexicons.

Result of positive text
Lexicon Precision Recall F1
NTUSD 0.603 0.375 0.462
HowNet 0.728 0.540 0.620
DUT 0.721 0.552 0.593
SentiRuc (before disambiguation) 0.744 0.588 0.657
SentiRuc (after disambiguation) 0.782 0.678 0.726

Result of negative text
Lexicon Precision Recall F1

NTUSD 0.480 0.319 0.383
HowNet 0.611 0.451 0.519
DUT 0.572 0.445 0.501
SentiRuc (before disambiguation) 0.633 0.468 0.538
SentiRuc (after disambiguation) 0.671 0.589 0.627