## 3 Research Methodology
### Dataset
#### 3.2.2 Global Terrorism Database Dataset  
The Global Terrorism Database is a dataset on terrorist activities that started in 1970. The dataset was obtained from Kaggle [45]. The current version has recorded over 150,000 cases of armed violence committed worldwide during this period. Processes to generate the database rely on using encoded data about the locations, weapons, types of offences (such as facilities or individuals), and unique group or category identifiers similar to those used in traffic datasets. At the core of the database are basic surface features. The dataset includes several pertinent fields related to terrorism terminology, specifically: \"attacktype1_txt\", \"target1\", \"addnotes\", \"scite1\", \"scite2\", \"scite3\", and \"dbsource\". The column \"attacktype1_txt\" classifies the principal method of attack, offering insights into prevalent tactics employed in terrorist activities. The column \"target1\" outlines the primary objective of the attack, providing context for its intent and frequently correlating with the perpetrator's goals. The \"addnotes\" column offers more notes or details regarding the attack that may not be comprehensively represented in other columns. It frequently encompasses information regarding the conditions, reasons, or background that elucidates the incident comprehensively. The columns \"scitel\", \"scite2\", and \"scite3\" represent citations or sources from which information regarding the occurrence was acquired. They may encompass citations from news articles, reports, or other sources that validate or expound upon the incident's particulars. A \"dbsource\" column exists that designates the source \begin{table}
\begin{tabular}{c c c} \hline \hline
**Term** & **TF-IDF** & **Number of Document** \\ \hline Extremism & 0.042 & 251 \\ \hline Radicalization & 0.037 & 140 \\ \hline Insurgency & 0.033 & 147 \\ \hline Counterterrorism & 0.044 & 153 \\ \hline Violence & 0.039 & 149 \\ \hline Hostage & 0.029 & 133 \\ \hline Conflict & 0.035 & 146 \\ \hline Military & 0.032 & 144 \\ \hline Homeland Security & 0.038 & 139 \\ \hline Cyberterrorism & 0.03 & 137 \\ \hline Bombing & 0.045 & 252 \\ \hline Attack & 0.034 & 142 \\ \hline Terror Cell & 0.043 & 143 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Terms and their TF-IDF extracted. database or collection utilized to compile the attack information. It can indicate whether the data originated from GTD's primary data collection or external sources, hence assisting in tracking data provenance. This research extracts the TF-IDF of the terms within the dataset, with selected entries displayed in Table 3. The GTD underscores the significance of these terms in monitoring global terrorism trends, demonstrating the intricate and enduring characteristics of specific attack types and targets across time. These terms highlight global terrorist patterns, emphasizing attack methodologies, target categories, and active regions within the extensive GTD dataset. A specific \"co-occurrence\" has been established inside the dataset. This analysis successfully extracted the co-occurrence of these terms (see Table 4). \begin{table}
\begin{tabular}{l l} \hline \hline
**Term** & **Frequent Co-Occurrence Word** \\ \hline Bombing/Explosion & Attack \\ \hline Armed Assault & Firearm \\ \hline Suicide Attack & Casualty \\ \hline Civilians & Victims \\ \hline Military & Conflict \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Terms and their co-occurrence from GTD dataset.