## 5 Experimental Results
### Comparative Evaluation of faSTNT and TextNetTopics Performance  
This section compares the performance of faSTNT with a 60% feature-discarding rate against TextNetTopics for the WOS-5376 and LitCovid datasets. Additionally, it evaluates the performance of faSTNT with a 40% feature-discarding rate against TextNetTopics for the MultiLabel and arXiv datasets. The chosen \(\
u\%\) values for faSTNT (60% and 40%) are based on their ability to yield maximum performance comparable to TextNetTopics, as demonstrated in the previous section. As shown in Tables 1-3, faSTNT demonstrates superior performance across various performance metrics (i.e., accuracy, f1-score, precision, recall, AUC) along different aggregated top-ranked topic clusters derived from four datasets (WOS-5736, LitCovid, MultiLabel, and arXiv). Additionally, faSTNT achieves similar or higher performance than TextNetTopics with significantly fewer features. \begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline  & \multicolumn{2}{c}{**Accumulated Topics**} & \multirow{2}{*}{**Words**} & \multirow{2}{*}{**Accuracy**} & \multirow{2}{*}{**Recall**} & \multirow{2}{*}{**Specificity**} & \multirow{2}{*}{**F-Measure**} & \multirow{2}{*}{**AUC**} & \multirow{2}{*}{**Precision**} & \multicolumn{2}{c}{**Cohen’s Kappa**} \\ \hline \multirow{8}{*}{**F1-score**} & 1 & 19.3 & 86.4 & 81.3 & 91.6 & 85.6 & 90.3 & 90.5 & 72.9 \\  & 2 & 28 & 86.9 & 82.9 & 90.8 & 86.3 & 91.3 & 89.9 & 73.7 \\  & 3 & 42.5 & 90.1 & 88.2 & 91.9 & 89.7 & 94.6 \begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline  & \multicolumn{2}{c}{**Accumulated Topics**} & \multicolumn{1}{c}{**Words**} & \multicolumn{1}{c}{**Accuracy**} & \multicolumn{1}{c}{**Recall**} & \multicolumn{1}{c}{**Specificity**} & \multicolumn{1}{c}{**F-Measure**} & \multicolumn{1}{c}{**AUC**} & \multicolumn{1}{c}{**Precision**} & \multicolumn{1}{c}{**Cohen’s Kappa**} \\ \hline \multirow{9}{*}{**Counoun**} & 1 & 4.9 & 79.3 & 61.9 & 96.3 & 74.6 & 80.1 & 94.5 & 58.4 \\  & 2 & 9.8 & 87.3 & 81.2 & 93.4 & 86.3 & 89.6 & 92.5 & 74.6 \\  & 3 & 14.5 & 90.5 & 87.5 & 93.5 & 90.1 & 93.2 & 93.0 & 81.0 \\  & 4 & 19.2 & 91.7 & 89.3 & 94.0 & 91.4 & 94.2 & 93.7 & 83.4 \\  & 6 & 28.7 & 94.2 & 93.8 & 94.6 & 94.2 & 97.2 & 94.5 & 88.4 \\  & 8 & 37.5 & 94.9 & 95.3 & 94.6 & 95.0 & 98.3 & 94.5 & 89.8 \\  & 10 & 46.2 & 95.7 & 96.1 & 95.4 & 95.7 & 98.8 & 95.4 & 91.5 \\  & 12 & 54.4 & 96.0 & 96.6 & 95.5 & 96.0 & 99.0 & 95.5 & 92.1 \\  & 14 & 63.1 & 96.6 & 97.1 & 96.1 & 96.6 & 99.2 & 96.1 & 93.2 \\  & 16 & 71.6 & 96.8 & 97.3 & 96.2 & 96.8 & 99.4 & 96.2 & 93.6 \\  & 18 & 80 & 97.0 & 97.8 & 96.3 & 97.0 & 99.5 & 96.4 & 94.1 \\  & 20 & 88 & 96.9 & 97.5 & 96.3 & 96.9 & 99.5 & 96.3 & 93.9 \\ \hline \multirow{9}{*}{**Coun**} & 1 & 6 & 76.3 & 75.2 & 77.4 & 76.0 & 80.1 & 77.0 & 52.7 \\  & 2 & 12 & 81.6 & 81.9 & 81.3 & 81.6 & 86.8 & 81.4 & 63.2 \\  & 3 & 18 & 84.3 & 85.5 & 83.0 & 84.4 & 91.0 & 83.4 & 68.5 \\  & 4 & 24 & 86.2 & 87.1 & 85.3 & 86.3 & 92.5 & 85.5 & 72.4 \\  & 6 & 36 & 87.7 & 88.9 & 86.6 & 87.8 & 94.1 & 86.8 & 75.4 \\  & 8 & 48 & 88.9 & 89.9 & 87.9 & 89.0 & 95.1 & 88.1 & 77.8 \\  & 10 & 60 & 89.5 & 89.9 & 89.1 & 89.5 & 95.8 & 89.1 & 79.0 \\  & 12 & 72 & 90.1 & 90.3 & 89.9 & 90.1 & 96.2 & 89.9 & 80.1 \\  & 14 & 84 & 90.4 & 90.9 & 89.9 & 90.5 & 96.5 & 90.0 & 80.9 \\  & 16 & 96 & 90.5 & 91.1 & 90.0 & 90.6 & 96.5 & 90.1 & 81.1 \\  & 18 & 108 & 90.9 & 91.6 & 90.3 & 91.0 & 96.7 & 90.4 & 81.9 \\  & 20 & 120 & 90.8 & 91.7 & 89.9 & 90.9 & 96.9 & 90.1 & 81.6 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Performance metrics of faSTNT with 60% feature discarding utilizing WOS-5736 and LitCovid datasets.