Baekdudaegan is a protected mountain range that spans 1,400 km across the Korean Peninsula and serves as a hub of biodiversity and cultural heritage. This study presents a comprehensive analysis of research insights into this complex mountain ecosystem through bibliometric analysis and Latent Dirichlet Allocation (LDA) topic
modelling approaches using metadata from 165 scholarly publications sourced from the Web of Science (WoS) core collection. We observed a discernible upward trend in Baekdudaegan-related literature, with a notable surge in scholarly interest post2017, primarily from institutions such as the Baekdudaegan National Arboretum and the Korea National Arboretum. According to WoS categories, the examined research was dominated by plant science, ecology and environmental science clusters. Employing the LDA model to the corpus of texts extracted from keywords and abstracts
of each observed literature, we identified six principal research topics: biochemical pathways, forest ecosystem dynamics, genomic taxonomy, seedling dynamics, biodiversity conservation and climate change. Finally, we visualized the keyword network and LDA-trained word cloud topics. The findings of this study enhance a deeper understanding of Baekdudaegan Mountains research, offering valuable insights for researchers and policymakers. This study serves as a resource for future investigations and informed decision-making regarding the sustainable management of mountain ecosystems. [For supplement see https://austriaca.at/Dhakal_et_al.xlsx]
Schlagworte: Baekdudaegan, Biodiversity, Latent Dirichlet Allocation, Sustainable development goals, text mining
Thakur Dhakal - Tae-Sue Kim - Shraddha Tiwari - Seong-Hyeon Kim - Anteneh Bongasie - Jun-Young Kim - Gab-Sue Jang - Su-Jin Kim