Spatial heterogeneity analysis of marine influence on China

Objective/Introduction The ocean has exerted a growing influence on human societal development over time. Investigating this influence at the national level is essential for informed marine spatial planning and policy-making. However, empirical assessments are often constrained by the scarcity and unstructured nature of relevant data. Methods To address this gap, this study proposes an innovative analytical framework that integrates latent Dirichlet allocation (LDA) topic modeling with complex network theory. Using Internet-based marine news big data, we systematically evaluate the impact of the ocean on China across three analytical dimensions: spatial differentiation, agglomeration characteristics, and diffusion pathways. Accordingly, we construct three complex networks—namely, the network of ocean impact on China, the sea-rail intermodal transport network, and the marine ecology network—to capture the interregional associations among urban marine activities, including economy, transportation, culture, and ecology. Results The findings reveal three key insights. (i) The influence of the ocean on China exhibits pronounced regional heterogeneity. (ii) Cities affected by similar marine activities are broadly clustered into three networked regions: the Bohai Rim region, the Yangtze River Delta region, and the Pan-Pearl River Delta region. (iii) The impact extends from coastal to inland areas through three primary diffusion modes, i.e., sea-rail multimodal transport, marine culture dissemination, and marine ecological connectivity. Discussion/Conclusion This study offers a scalable and data-driven paradigm for assessing marine influence using unstructured media data. The proposed framework provides valuable references for marine spatial planning and regional coordination, and it can be adapted to other countries or regions facing similar data limitations.