In this study, we examine interspecific relationship patterns by analyzing the Plants Social Network (PSN) structure of evergreen broad-leaved forests in Jeollanam-do, South Korea. We established a total of 104 quadrats across seven regions where evergreen broad-leaved species are stably distributed in Jeollanam-do. All woody plant species occurring within the quadrats were surveyed. We excluded low-frequency species with an expected frequency below 5% and used the chi-square statistic to analyze interspecific association. A sociogram focusing on positive associations between species pairs was constructed, and Gephi 0.10 was used to conduct network structure analyses that included centrality measures. The sociogram was classified into four major groups that reflect the fundamental and realized niche of the component species. In terms of network centrality, Parthenocissus tricuspidata, Mallotus japonicus, Acer pseudosieboldianum, and Quercus serrata showed high degree centrality. Closeness centrality was high in P. tricuspidata, Ficus oxyphylla, Elaeagnus macrophylla, and Q. salicina. Betweenness centrality was high in P. tricuspidata, M. japonicus, A. pseudosieboldianum, and Q. serrata, whereas eigenvector centrality was high in F. oxyphylla, E. macrophylla, Styrax japonicus, and Gardneria nutans. The k-core analysis indicated that the 7-core group included Fatsia japonica, F. oxyphylla, E. glabra, E. macrophylla, Euonymus japonicus, Stauntonia hexaphylla, Hedera rhombea, and Rhaphiolepis indica var. umbellata. Compared to those of previous studies, the network structure showed relatively low cohesion. From these results, we recommend strategies that can restore and enhance the diversity and structural stability of evergreen broad-leaved forests.