Katsumori Matsushima

TL;DR: The results showed that topological measures are beneficial in detecting branching innovation in the citation network of scientific publications.

TL;DR: In this article, a topological clustering method is used to detect the sub-domains of sustainability science, and the existence of 15 main research clusters: Agriculture, Fisheries, Ecological Economics, Forestry (agroforestry), Forestry (tropical rain forest), Business, Tourism, Water, Forest (biodiversity), Urban Planning, Rural Sociology, Energy, Health, Soil and Wildlife.

TL;DR: This analysis confirms that the fuel cell and solar cell are rapidly growing domains in energy research, and investigates the detailed structure of these two domains by clustering publications in these domains by using citation network analysis.

TL;DR: Direct citation, which could detect large and young emerging clusters earlier, shows the best performance in detecting a research front, and co-citation shows the worst, which suggests that the content similarity of papers connected by direct citations is the greatest and that direct citation networks have the least risk of missing emerging research domains.

TL;DR: The method divides citation networks into clusters using the topological clustering method, track the positions of papers in each cluster, and visualize citation networks with characteristic terms for each cluster to determine whether there are emerging knowledge clusters.