Table 7.
Detection model performance with the depression-domain lexicon.
| Detection model | Precision | Recall | F1 | Accuracy |
| NBa | 67% | 67% | 67% | 67% |
| Lb-NB | 74% | 73% | 73% | 73% |
| LRc | 76% | 76% | 75% | 76% |
| L-LR | 77% | 77% | 77% | 77% |
| RFd | 68% | 68% | 68% | 68% |
| L-RF | 77% | 77% | 76% | 77% |
| SVMe | 65% | 65% | 65% | 65% |
| L-SVM | 74% | 72% | 72% | 72% |
| DTf | 67% | 67% | 67% | 67% |
| L-DT | 69% | 69% | 69% | 69% |
aNB: naive Bayes.
bL: depression-domain lexicon as a feature.
cLR: logistic regression.
dRF: random forest.
eSVM: support vector machine.
fDT: decision tree.