## 3 The Results of the Bibliometric Analysis
### Social Structure Analysis
#### 3.2.2 Institutions Analysis  
A total of 474 institutions were involved with the 402 documents in this study. Figure 6 illustrates the collaborative networks among institutions that have published more than two articles related to USV, with a total of 54 institutions meeting the threshold. In a manner similar to Section 3.1, Figure 6 delineates clusters of these institutions based on the strength of their collaborative ties. The size of the nodes in these network representations corresponds to the number of articles these institutions have contributed to the domain within our dataset. The lines connecting these nodes signify instances of collaboration among these institutions. The thicker the line, the more jointly authored articles the two connected institutions have published. Nodes sharing the same color indicate a higher level of collaboration in the new technology of USV research compared to others. The detailed setting for the parameters used for the figure was provided in Appendix A Table A2. Figure 6 provides further insights into the collaborative research field, particularly highlighting the significant role of Dalian Maritime University. This institution stood out as the most prolific contributor, with a total of six collaborative links and 31 documents, primarily from Dalian Minzu University, UCL (University College London) and Southeast University. Notably, Dalian Maritime University also engaged in partnerships with universities in nearby northern cities, primarily Beijing and Harbin, thanks to their geographical proximity. Consequently, Dalian Maritime University served as the central hub within the green cluster due to these collaborative connections. Deduced from the light blue cluster, UCL, a university with the most productive author, acted as an important channel to conduct collaborative research with other institutions. As for the blue cluster, the institutions within this group were primarily situated near the ocean, encompassing  
Figure 6: The network of institution collaboration using analysis of the co-authorship. areas like Zhejiang, Qingdao and Shanghai. In this cluster, Harbin Engineering University emerged as the focal point of collaborative activities. The yellow cluster, on the other hand, shows the strong link between Chinese institutions and European institutions, with Wuhan University of Technology playing a central role. Of particular interest was the fact that Polish Naval Academy had established connections with institutions in different regions, as it had 21 total link strengths, facilitated through its partnership with University of New Hampshire (UNH). Hence, UNH, became a crucial link in the red cluster, components of which were tightly intertwined and supported with each other and display a lasting and practical cooperation relationship. Lastly, the purple cluster consists of universities and research institutions in America, Singapore and Italy, etc., with National University of Singapore acting as the core of this cluster. Among these institutions, Dalian Maritime University demonstrated the highest level of productivity, having authored 31 research papers. It was followed by Harbin Engineering University with 21 publications, Chinese Academy of Science with 15 and University College London with 13 publications. As evidenced in authors' analysis in Section 3.1, University College London had a dedicated team engaged in USV research, playing a central role in this specific domain. Furthermore, in accordance with Table 2, Shanghai Jiaotong University and Shanghai Maritime University were the top two institutions with the latest and highest average publication year, denoting that they were conducting most of the new technology research in recent years and paying sufficient attention to the burgeoning development of USVs. In spite of comparatively high total publications, institutions such as Shenyang Institute of Autonomous CAS, Gdynia Maritime University and Chinese Academy of Science embody an old APY of 2015.7, 2014.1 and 2015.8, respectively.