## 3 Dataset Analysis
### Authors  
When it comes to author analysis, the most relevant authors will be examined, including the top 20 authors' production over time, the top 20 most relevant affiliations, and the top 20 most relevant corresponding author's countries. Regarding the top 20 relevant authors, according to Figure 10, [PERSON] stands out with 8 articles, followed by [PERSON], [PERSON], and [PERSON] with 4 articles each. Figure 8: Journals’ impact based on H-index. Figure 9: Journals’ growth (cumulative) based on the number of papers. In Figure 11, we display the publication frequency of various authors across different years. For example, [PERSON] has published three articles, one in each of the years 2018, 2019, and 2020. The author has received 13 citations, with a yearly citation average of 2.16. Additionally, author [PERSON] has published 8 articles, one of which was cited in 2019 a total of 30 times, averaging 2 citations per year. In 2017, there was an article with 20 citations, and in 2018, there was another article with 19 citations. Similarly, in 2019, another article had a total of 13 citations. In 2021, [PERSON] published 4 articles, accumulating a total of 16 citations, with an average yearly citation of 5.33. In the context of our study, the most relevant affiliations, based on the number of articles, are represented in Figure 12. These affiliations have shown significant productivity in the fields of AI and ABM, contributing to the breadth and depth of research on the subject. In the context of our research, focusing on the use of AI in ABM applications, the most relevant countries, based on the number of articles and various metrics, are represented in Figure 13.  
These countries, particularly the USA, China, UK, Canada, and Germany, have demonstrated notable contributions to research in the fields of AI and ABM. The SCP (single country publications) and MCP (multiple country publications) metrics provide insights into the collaborative nature of publications, and the frequency and MCP ratio offer additional perspectives on the distribution and collaboration patterns. The map in Figure 14 illustrates the distribution of scientific production across various countries. The intensity of the blue color on the map corresponds to the volume of scientific production for each country. A darker shade of blue indicates a higher number of publications, while a lighter shade represents a lower number of publications. In this visual representation, the color gradient serves as a quick reference to assess the relative research output across different countries. It is evident that certain countries dominate the research landscape, while others make more modest contributions. Additionally, regional trends and relationships between regions can be observed based on the frequency of scientific production. Furthermore, it is notable that the USA dominates scientific production, indicating a significant contribution to global research. Figure 10: Top-20 authors based on number of documents. In order to analyze and classify the data underlying Figure 13, a Pareto ABC Diagram was created. This method is based on Pareto's Principle, which states that, in many situations, approximately 80% of results come from 20% of causes [63]. In the context of Pareto ABC analysis, this means that a small number of elements contribute significantly to the total, while the majority of elements contribute less. The primary objective of ABC analysis is to prioritize stringent control for class A items, implement less rigorous control for class B items, and exert minimal control for class C items [64]. According to the representation in Figure 15, class A represents 81% of the contribution to global scientific production. This category includes countries such as the USA, UK, China, Canada, Germany, and Saudi Arabia, and they are the most important countries in this field. Special attention should be given to collaborations, resource exchange, and partnerships to maintain and enhance their impact.