Abstract
Sustainability science has been widely accepted worldwide as an important research field worldwide. Since it is widespread in many research fields such as environmental science and engineering, architecture, materials science, and civil engineering, it is important to discover the hidden connections between sustainability science and other academic fields. For this purpose, supporting tools are necessary. This paper investigates the relationship between sustainability science and complex networks on the basis of citation network analysis using large datasets of academic papers. First, citation networks are generated on the basis of academic paper datasets and clustered to understand the research fields of sustainability science and complex networks. Next, we measure the textual similarities among the clusters in these fields and analyse the shared terms to find the overlapping research areas that connect the two fields. These results offer overviews of how complex networks contribute to sustainability science and assist the formation of policies that promote key results in artificial intelligence toward future sustainable societies.
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