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 |