# Leveraging Large Language Models for Enhancing Safety in Maritime Operations
## 2 Methodology of Literature Review
### Citation Trends  
A citation analysis was conducted to evaluate the influence and prominence of selected studies on the application of Large Language Models (LLMs) in maritime safety. The analysis aimed to move beyond a descriptive overview and provide deeper insights into the research landscape, including its evolution, geographical distribution, and emerging thematic trends. The data were retrieved from Scopus and Google Scholar using a structured search query: ALL (llms OR llm AND maritime AND safety) AND PUBYEAR > 2010 AND PUBYEAR < 2025 (available at: [[https://www.scopus.com/term/analyzer.uri?sort=plf-f&scr=&ssfid=5747d4656b812](https://www.scopus.com/term/analyzer.uri?sort=plf-f&scr=&ssfid=5747d4656b812) cc22d3221 cac6078 fdd&sot=&ssf=4 ssl=78&s=ALL]([https://www.scopus.com/term/analyzer.uri?sort=plf-f&scr=&ssfid=5747d4656b812](https://www.scopus.com/term/analyzer.uri?sort=plf-f&scr=&ssfid=5747d4656b812) cc22d3221 cac6078 fdd&sot=&ssf=4 ssl=78&s=ALL)(llms+OR +llm+AND+maritime+AND+safety)+AND+PUBYEAR+%3E+2009+AND+PUBYEAR+%3 C+2025&origin=resultslist&count=10&analyzeResults=Analyze+results, accessed on 1 January 2025), ensuring that only relevant publications within the maritime and AI domains were considered. Citation counts and publication trends were extracted directly from Scopus's citation tracking tools, and country-specific contributions were analyzed based on author affiliations reported in indexed databases. The analysis of publication frequency over time (Figure 3) reveals a significant acceleration in research interest from 2020 onward, with the highest number of publications recorded in 2024 (43 documents). Between 2010 and 2019, research activity remained sporadic, with fewer than 10 publications annually, indicating that the integration of LLMs into maritime safety was not a widely explored area. However, from 2020 onward, the number of studies began to rise sharply, suggesting that the advent of more powerful LLMs,such as GPT-3 (2020) and GPT-4 (2023), catalyzed interest in their applications within maritime contexts. The data indicate that the growing volume of research aligns with global advancements in artificial intelligence and increasing regulatory attention toward maritime digitalization. The sharp rise in publications from 2023 to 2024 highlights an inflection point where LLMs moved beyond theoretical discussions into practical implementation studies, reflecting their emerging role in operational risk assessment, compliance automation, and decision support systems. The geographical distribution of publications provides insight into the key contributors to this field. China leads with 19 publications, followed by the United Kingdom (13), the United States (10), and Australia (6). This trend suggests that AI-driven maritime safety research is being driven primarily by technologically advanced economies with significant investments in AI and maritime infrastructure. The presence of China as the most prolific contributor aligns with its broader national AI strategy and rapid digitalization of its shipping industry. European countries, including Poland (5), Greece (4), the Netherlands (4), and Norway (4), also demonstrate substantial contributions, which may be linked to the EU's initiatives on maritime safety and AI governance. Similarly, Malaysia (5) and India (4) highlight emerging AI research hubs in the Asia-Pacific region. The relatively lower representation of traditionally strong maritime nations such as Japan (1), Germany (2), and France (1) suggests that LLM research in these countries is still in its early stages or embedded within broader AI and automation research agendas rather than dedicated maritime AI applications. The citation analysis further validates the growing recognition of LLMs in maritime safety. Between 2010 and 2019, citations remained relatively low, reflecting the limited number of studies available during this period. However, from 2020 onward, a sharp increase in citations is observed, with the most significant jump occurring in 2024 (238 citations).