## 4 Results
### Training Experiments
* qarib/bert-base-qarib Embedding: With this embedding, cleaning provided the highest coherence (0.144) and excellent topic diversity (0.900). Stemming also performed well, maintaining high diversity and coherence close to that obtained after cleaning. While BERTopic demonstrated overall superior performance, specific scenarios highlighted its limitations, particularly evident in the observed negative NPMI scores during the experiments. These scores were primarily attributed to certain embedding-stemmer combinations and insufficient pre-processing strategies. For instance, when UBC-NLP/MARBERT embeddings were paired with the Tashaphyne stemmer, the aggressive stemming excessively reduced context-rich terms, leading to fragmented clusters and incoherent topics. Similarly, embeddings like xlm-roberta-base, when applied to minimally pre-processed \begin{table}
\begin{tabular}{c l l c c c} \hline \hline  & **Embedding Model** & **Pre-Processing** &
\begin{tabular}{c} **NPMI Coherence** \\ **Score \(\uparrow\)** \\ \end{tabular} & **Topic Diversity** & **Training Time** \\ \hline
1 & &
\begin{tabular}{c} Original articles (without \\ pre-processing) \\ \end{tabular} & 0.062 & 0.814 & 3096.04 \\ \hline
2 & UBC-NLP/ &
\begin{tabular}{c} Cleaning \\ \end{tabular} & 0.110 & 0.871 & 2419.38 \\ \hline
3 & &
\begin{tabular}{c} Cleaning + stemming (Tashaphyne) \\ \end{tabular} & \(-0.004\) & 0.857 & 2273.24 \\ \hline
4 & &
\begin{tabular}{c} Cleaning + stemming (ISRI) \\ \end{tabular} & 0.046 & 0.886 & 2187.69 \\ \hline
5 & &
\begin{tabular}{c} Original articles (without \\ pre-processing) \\ \end{tabular} & \(-0.088\) & 0.743 & 2235.53 \\ \hline
6 & xlm-roberta-base &
\begin{tabular}{c} Cleaning \\ \end{tabular} & 0.107 & 0.843 & 1974.42 \\ \hline
7 & &
\begin{tabular}{c} Cleaning + stemming (Tashaphyne) \\ \end{tabular} & 0.104 & 0.800 & 1730.37 \\ \hline
8 & &
\begin{tabular}{c} Cleaning + stemming (ISRI) \\ \end{tabular} & 0.083 & 0.829 & 1695.86 \\ \hline
9 & &
\begin{tabular}{c} Original articles (without \\ pre-processing) \\ \end{tabular} & 0.024 & 0.757 & 1653.41 \\ \hline
10 & \
\begin{tabular}{c} abumindlab/ \\ bert-base-araherty02 \\ \end{tabular} &
\begin{tabular}{c} Cleaning \\ \end{tabular} & 0.120 & 0.843 & 1390.71 \\ \hline
11 & &
\begin{tabular}{c} Cleaning + stemming (Tashaphyne) \\ \end{tabular} & 0.074 & 0.800 & 683.57 \\ \hline
12 & &
\begin{tabular}{c} Cleaning + stemming (ISRI) \\ \end{tabular} & 0.022 & 0.771 & 642.83 \\ \hline
13 & &
\begin{tabular}{c} Original articles (without \\ pre-processing) \\ \end{tabular} & \(-0.040\) & 0.857 & 1688.56 \\ \hline
14 & \
\begin{tabular}{c} CAMeL-Lab/ \\ bert-base/arabic/ \\ camelbert-da \\ \end{tabular} &
\begin{tabular}{c} Cleaning \\ \end{tabular} & **0.211** & 0.886 & 1386.45 \\ \hline
15 & &
\begin{tabular}{c} Cleaning + stemming (Tashaphyne) \\ \end{tabular} & 0.139 & 0.843 & 1259.72 \\ \hline
16 & &
\begin{tabular}{c} Cleaning + stemming (ISRI) \\ \end{tabular} & 0.062 & 0.814 & 1225.23 \\ \hline
17 & &
\begin{tabular}{c} Original articles (without \\ pre-processing) \\ \end{tabular} & 0.126 & 0.843 & 3216.70 \\ \hline
18 & \
\begin{tabular}{c} asafaya/ \\ bert-base-arabic \\ \end{tabular} &
\begin{tabular}{c} Cleaning \\ \end{tabular} & 0.120 & 0.886 & 2725.64 \\ \hline
19 & &
\begin{tabular}{c} Cleaning + stemming (Tashaphyne) \\ \end{tabular} & 0.089 & 0.871 & 2486.15 \\ \hline
20 & &
\begin{tabular}{c} Cleaning + stemming (ISRI) \\ \end{tabular} & 0.081 & 0.871 & 1240.58 \\ \hline
21 & &
\begin{tabular}{c} Original articles (without \\ pre-processing) \\ \end{tabular} & \(-0.026\) & 0.786 & 861.80 \\ \hline
22 & \
\begin{tabular}{c} qarib/bert-base-qarib \\ \end{tabular} &
\begin{tabular}{c} Cleaning \\ \end{tabular} & 0.144 & 0.900 & 711.71 \\ \hline
23 & &
\begin{tabular}{c} Cleaning + stemming (Tashaphyne) \\ \end{tabular} & 0.138 & 0.900 & 1238.11 \\ \hline
24 & &
\begin{tabular}{c} Cleaning + stemming (ISRI) \\ \end{tabular} & 0.131 & 0.871 & 1177.52 \\ \hline \hline \end{tabular}
\end{table}