Research Article
[Retracted] Sentiment Analysis on COVID-19 Twitter Data Streams Using Deep Belief Neural Networks
Table 3
Classifier accuracy comparison with the proposed method.
| N-gram | Type of attribute | Classifier accuracy | Proposed DBN (%) | Naïve Bayes (%) | SVM (%) | K-nearest neighbors (%) |
| Unigram | All twitter data | 80.3 | 79.4 | 81.9 | 73.3 | Information gain >0 | 84.1 | 86.6 | 83.6 | 74.2 | Best 70% on ranking | 88.1 | 88.0 | 83.2 | 73.5 |
| Bigram | All twitter data | 86.1 | 75.2 | 85.8 | 62.7 | Information gain >0 | 90.3 | 89.0 | 82.8 | 63.3 | Best 70% on ranking | 89.5 | 83.0 | 87.8 | 62.7 |
| 1 to 3 gram | All twitter data | 86.1 | 85.7 | 82.5 | 68.8 | Information gain >0 | 90.1 | 92.5 | 84.1 | 66.0 | Best 70% on ranking | 89.0 | 88.3 | 83.8 | 66.4 |
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