## 4 Results
### Results of Keyword Centrality Analysis  
A keyword centrality analysis was conducted to identify the most influential terms in research related to GAI and security. This analysis utilized three centrality measures: degree centrality, closeness centrality, and betweenness centrality, as summarized in Table 3.  
Degree centrality quantifies the number of direct connections that a keyword has within the research network, reflecting its prominence. The term \"ChatGPT\" emerges with the highest degree centrality score (0.93878), making it the most connected and central keyword in the network. It is followed closely by \"AI\" (0.87755) and \"model\" (0.81633), both of which also exhibit strong connectivity, signifying their prominent presence in the research corpus. Other keywords, including \"result\" (0.81633), \"datum\" (0.79592), and \"LLM\" (0.77551), also display high degree centrality, reflecting their frequent co-occurrence with other terms and their integral role in the discourse surrounding GAI and security.  
Closeness centrality measures how easily a keyword can connect to all other keywords in the network, providing insight into its accessibility and influence. The term \"model\" ranks highest in closeness centrality (0.67606), indicating that it is central to the network and can be quickly connected to other keywords. Other highly ranked terms include \"language\" (0.5931) and \"LLM\" (0.28357), which play key roles in bridging various concepts within the GAI and security discourse. Interestingly, despite its high degree centrality, \"ChatGPT\" has a relatively lower closeness centrality (0.25657), suggesting that although it is frequently mentioned, its connections are less direct or influential in linking other topics within the network. This finding implies that while \"ChatGPT\" is an essential term, it does not serve as a primary hub for reaching other keywords in the network.  
Betweenness centrality assesses how effectively a keyword acts as a bridge, facilitating connections between different groups of keywords. \"ChatGPT\" once again leads with the highest betweenness centrality (0.02865), underscoring its role as a key connector in the research landscape. \"AI\" (0.02539) and \"result\" (0.02225) also play vital bridging roles, helping to link different research topics and clusters. Other terms, such as \"datum\" (0.01983), \"model\" (0.01907), and \"technology\" (0.01786), exhibit strong betweenness centrality, indicating their importance in connecting different research areas within the broader GAI and security domain.  
In summary, this analysis highlights the varying roles of \"ChatGPT\", \"AI\", and \"model\" within the research network. While \"ChatGPT\" and \"AI\" are highly connected and serve as important bridges within the research landscape, \"model\" stands out in terms of accessibility, playing a crucial role in directly linking different keywords across the landscape. The prominence of terms like \"technology\", \"LLM\", and \"analysis\" across all centrality measures emphasizes their significant contributions to discussions of GAI and security, further illustrating the complexity and interconnectedness of research topics in this field.