Research Article
An Efficient Sentiment Classification Method with the Help of Neighbors and a Hybrid of RNN Models
Table 3
The effect of the neighborhood technique.
| Neighboring | Metrics | Dataset | BG | BIS | MVSA-Single | Twitter | IMDB |
| Not taken into account | Accuracy | 98.23 | 97.54 | 80.77 | 95.14 | 86.65 | Precision | 98.46 | 98.29 | 80.20 | 95.18 | 89.45 | Recall | 98.15 | 96.21 | 80.79 | 95.14 | 82.41 | F1-score | 98.10 | 97.95 | 80.11 | 95.11 | 86.01 |
| Taken into account | Accuracy | 99.60 | 98.32 | 82.19 | 96.13 | 87.60 | Precision | 99.55 | 99.51 | 82.39 | 96.12 | 91.06 | Recall | 99.65 | 97.54 | 82.16 | 96.13 | 83.64 | F1-score | 99.60 | 98.52 | 82.22 | 96.12 | 87.20 |
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Bold values indicate that the proposed neighbourhood technique model has achieved better results.
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