## 4 Results and Discussion
### F1-Score Variants
This signifies low model performance. In this case, the micro F1-score outperforms the macro and weighted F1-scores, and none of the three metrics reach the benchmark value of 0.53. Similarly, when applying the aggregated GoEmotions lexicon to the aggregated XED dataset, the results consistently show a lower macro F1-score that does not reach the threshold of 0.53 (see Figure 17b and Table 7). In this case, the micro and weighted F1-scores are higher and surpass the 0.53 threshold. The behavior of the micro F1-score, as observed in Figures 14 and 17, reflects its sensitivity to class imbalance. This is noticeable when applying the GoEmotions lexicon to the balanced XED dataset, where the micro F1-score shows higher values compared to other F1 variants. This observation aligns with the characteristic of the micro F1-score of aggregating contributions from all classes, and then reflecting the overall performance more reliably when classes are balanced. The results confirm that the micro F1-score is an appropriate metric for datasets with balanced class distributions. Figure 16: Performance of GoEmotions distilled lexicon applied to GoEmotions dataset. (**a**) Chart that depicts micro, macro, and weighted F1-scores for the GoEmotions distilled lexicon, applied to the GoEmotions dataset across various thresholds; (**b**) chart that depicts micro, macro, and Weighted F1-scores for the GoEmotions Aggregated distilled lexicon, applied to the GoEmotions Aggregated dataset across various thresholds. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & \multicolumn{3}{c}{**XED Distilled Lexicon Applied to the**} & \multicolumn{3}{c}{**XED Aggregated Distilled Lexicon Applied**} \\  & \multicolumn{3}{c}{**GoEmotions Dataset**} & \multicolumn{3}{c}{**to the GoEmotions Aggregated Dataset**} \\ \hline
**Threshold** & **Macro F1** & **Micro F1** & **Weighted F1** & **Macro F1** & **Micro F1** & **Weighted F1** \\ \hline
0.000 & 0.271 & 0.310 & 0.504 & 0.508 & 0.530 & 0.588 \\ \hline
0.100 & 0.277 & 0.320 & 0.510 & 0.514 & 0.538 & 0.593 \\ \hline
0.200 & 0.290 & 0. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & \multicolumn{3}{c}{**GoEmotions Distilled Lexicon Applied to the**} & \multicolumn{3}{c}{**GoEmotions Aggregated Distilled Lexicon**} \\  & \multicolumn{3}{c}{**GoEmotions Dataset**} & \multicolumn{3}{c}{**Applied to the GoEmotions Aggregated Dataset**} \\ \hline
**Threshold** & **Macro F1** & **Micro F1** & **Weighted F1** & **Macro F1** & **Micro F1** & **Weighted F1** \\ \hline
0.000 & 0.272 & 0.310 & 0.503 & 0.510 & 0.531 & 0.588 \\ \hline
0.100 & 0.351 & 0.421 & 0.520 & 0.517 & 0.540 & 0.593 \\ \hline
0.200 & 0.462 & 0.514 & 0.565 & 0.537 & 0.569 & 0.605 \\ \hline
0.300 & 0.573 & 0.618 & 0.630 & 0.586 & 0.619 & 0.632 \\ \hline
0.400 & 0.643 & 0.681 & 0.677 & 0.647 & 0.676 & 0.676 \\ \hline
0.500 & 0.658 & 0.700 & 0.692 & 0.681 & 0.713 & 0.708 \\ \hline
0.600 & 0.660 & 0.732 & 0.716 & 0.710 & 0.757 & 0.746 \\ \hline
0.700 & 0.642 & 0.752 & 0.728 & 0.714 & 0.785 & 0.770 \\ \hline
0.800 & 0.601 & 0.738 & 0.710 & 0.686 & 0.768 & 0.751 \\ \hline
0.900 & 0.532 & 0.675 & 0.652 & 0.614 & 0.695 & 0.677 \\ \hline
1.000 & 0.452 & 0.480 & 0.480 & 0.486 & 0.498 & 0.497 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Evaluation metrics for the GoEmotions distilled lexicon applied to the GoEmotions Aggregated distilled lexicon applied to the GoEmotions Aggregated dataset.