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Figure 2:
Figure 3:
Figure 4:
Reviews classification per attraction_
| Attraction | Negative | Neutral | Positive | x̄ | s |
|---|---|---|---|---|---|
| Castelo de Bragança | 33 | 4 | 32 | 4.23 | 0.96 |
| Aldeia do Rio de Onor | 18 | 4 | 35 | 4.42 | 0.86 |
| Domus Municipalis | 11 | 1 | 3 | 3.73 | 1.03 |
| Cidadela de Bragança | 5 | 2 | 3 | 3.88 | 0.70 |
| Igreja de Santa Maria | 4 | 3 | 0 | 3.81 | 1.17 |
| Centro de Arte Contemporânea Graça Morais | 3 | 0 | 4 | 3.92 | 0.53 |
| Igreja da Antiga Sé | 4 | 3 | 0 | 3.87 | 0.53 |
| Museu Ibérico da Máscara e do Traje | 7 | 2 | 7 | 3.95 | 0.77 |
| Museu do Abade de Baçal | 3 | 1 | 3 | 3.96 | 1.15 |
| Parque Natural de Montesinho | 5 | 0 | 3 | 4.00 | 0.51 |
| Centro Ciência Viva | 2 | 1 | 6 | 4.02 | 1.39 |
| Centro de Interpretação da Cultura Sefardita do Nordeste Transmontano | 9 | 0 | 1 | 4.03 | 0.57 |
| Galeria Georges Dussaud | 0 | 0 | 3 | 4.05 | 0.00 |
| Museu Militar de Bragança | 9 | 3 | 9 | 4.04 | 1.20 |
Metrics report_
| Unigram Prediction Model | ||||
|---|---|---|---|---|
| Precision | Recall | F1-score | Support | |
| Negative | 0.48 | 0.50 | 0.49 | 114 |
| Neutral | 0.00 | 0.00 | 0.00 | 24 |
| Positive | 0.52 | 0.58 | 0.55 | 112 |
| Accuracy | 0.49 | 250 | ||
| Macro average | 0.33 | 0.36 | 0.35 | 250 |
| Weighted average | 0.45 | 0.49 | 0.47 | 250 |
| Bigrated Prediction Model | ||||
| Negative | 0.49 | 0.40 | 0.44 | 114 |
| Neutral | 0.18 | 0.17 | 0.17 | 24 |
| Positive | 0.51 | 0.61 | 0.55 | 112 |
| Accuracy | 0.47 | 250 | ||
| Macro average | 0.39 | 0.39 | 0.39 | 250 |
| Weighted average | 0.47 | 0.47 | 0.47 | 250 |
Stop words’ frequencies_
| Word | n |
|---|---|
| De | 466 |
| E | 361 |
| A | 305 |
| Que | 184 |
| O | 169 |
| É | 163 |
| Um | 148 |
| Uma | 147 |
| Muito | 145 |
| Com | 135 |
Calculation of accuracy, precision, and recall_
| Unigram Prediction Model | ||||
|---|---|---|---|---|
| Predicted | Negative | Neutral | Positive | All |
| Real | ||||
| Negative | 57 | 3 | 54 | 114 |
| Neutral | 17 | 0 | 7 | 24 |
| Positive | 44 | 3 | 65 | 112 |
| All | 118 | 0 | 126 | 250 |
| Bigrated Prediction Model | ||||
| Predicted | Negative | Neutral | Positive | All |
| Real | ||||
| Negative | 46 | 8 | 60 | 114 |
| Neutral | 14 | 4 | 6 | 24 |
| Positive | 34 | 10 | 68 | 112 |
| All | 94 | 22 | 134 | 250 |
Terms and their weights_
| Negative | Neutral | Positive | |||
|---|---|---|---|---|---|
| Algum | 0.63 | Fech | 0.50 | portug | 0.48 |
| Atra | 0.50 | Prox | 0.47 | lind | 0.46 |
| regia | 0.46 | Jardim | 0.45 | espanh | 0.45 |
| nad | 0.45 | Extern | 0.35 | otim | 0.43 |
| dent | 0.43 | Enriquec | 0.31 | bom | 0.43 |
| igreja | 0.42 | Muit | 0.31 | pesso | 0.40 |
| portugu | 0.42 | Espac | 0.29 | bem | 0.40 |
| esper | 0.40 | Atenc | 0.29 | val | 0.39 |
| eur | 0.39 | Garant | 0.28 | lindiss | 0.38 |
| monument | 0.38 | Indicaca | 0.28 | alem | 0.38 |
Sentiments’ classification_
| Rating (1–5) | Sentiment | n |
|---|---|---|
| 1–2 | Negative | 114 |
| =3 | Neutral | 24 |
| 4–5 | Positive | 112 |
| Total | 250 |