Table 5.
Ternary sentiment analysis results of the multi-modal model using the recurrent EEG decoding component.
Randomly initialized | GloVe | BERT | |||||||
---|---|---|---|---|---|---|---|---|---|
Model | P | R | F1 (std) | P | R | F1 (std) | P | R | F1 (std) |
Baseline | 0.408 | 0.384 | 0.351 (0.07) | 0.510 | 0.507 | 0.496 (0.06) | 0.722 | 0.714 | 0.710 (0.05) |
+ noise | 0.373 | 0.399 | 0.344 (0.10) | 0.531 | 0.519 | 0.504 (0.04) | 0.711 | 0.706 | 0.700 (0.06) |
+ ET | 0.424 | 0.413 | 0.388 (0.06) | 0.539 | 0.528 | 0.513 (0.04) | 0.728 | 0.717 | 0.714 (0.05) |
+ EEG full | 0.391 | 0.387 | 0.353 (0.07) | 0.505 | 0.505 | 0.488 (0.07) | 0.724 | 0.715 | 0.711 (0.06) |
+ EEG θ | 0.397 | 0.409 | 0.360 (0.07) | 0.516 | 0.510 | 0.498 (0.06) | 0.715 | 0.708 | 0.704 (0.05) |
+ EEG α | 0.390 | 0.390 | 0.347 (0.08) | 0.520 | 0.516 | 0.506 (0.05) | 0.720 | 0.712 | 0.707 (0.05) |
+ EEG β | 0.350 | 0.370 | 0.302 (0.09) | 0.523 | 0.519 | 0.509 (0.05) | 0.732 | 0.720 | 0.717 (0.07) |
+ EEG γ | 0.409 | 0.397 | 0.359 (0.07) | 0.517. | 0.513 | 0.502 (0.04) | 0.709 | 0.705 | 0.697 (0.06) |
+θ+α+β+γ | 0.401 | 0.400 | 0.368 (0.06) | 0.522 | 0.516 | 0.505 (0.05) | 0.722 | 0.717 | 0.713 (0.05) |
We report precision (P), recall (R), F1-score and the standard deviation (std) between five runs. The best results per column are marked in bold.