Research Article
Predicting the Currency Market in Online Gaming via Lexicon-Based Analysis on Its Online Forum
Table 5
Experimental results of predicted WoW token prices fluctuation.
| Learning method | Gradient boosting | Random forest | Support vector machine | Region | Learning days | Accuracy (%) | 1-score | MCC | Accuracy (%) | 1-score | MCC | Accuracy (%) | 1-score | MCC |
| North America region | 3 days | 75.65% | 0.7576 | 0.5731 | 69.13% | 0.6984 | 0.4799 | 64.13% | 0.6432 | 0.3445 | 5 days | 79.56% | 0.7955 | 0.5921 | 76.08% | 0.7784 | 0.5704 | 74.48% | 0.7539 | 0.318 | 7 days | 82.55 | 0.8255 | 0.6372 | 78.26% | 0.793 | 0.5768 | 76.95% | 0.7765 | 0.3106 | 12 days | 80.65% | 0.8045 | 0.6009 | 78.69% | 0.7858 | 0.579 | 78.69% | 0.7996 | 0.3773 |
| Europe region | 3 days | 69.56% | 0.6957 | 0.3917 | 71.52% | 0.7138 | 0.4375 | 75.43% | 0.7966 | ā0.0219 | 5 days | 71.73% | 0.7174 | 0.4346 | 73.91% | 0.7367 | 0.4907 | 70.65% | 0.6225 | 0.2742 | 7 days | 77.17% | 0.7718 | 0.5429 | 77.39% | 0.77 | 0.5723 | 71.3% | 0.6346 | 0.2989 | 12 days | 81.52 | 0.815 | 0.6322 | 77.6% | 0.7791 | 0.5779 | 73.91% | 0.6656 | 0.3416 |
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