Mapping knowledge landscapes across information ecosystems: a comparative scientometric analysis of cultural exchange and “community with a shared future” scholarship

Purpose This paper aims to investigate how the knowledge structure of a major global concept is organized, discovered and delivered across disparate scholarly information ecosystems. Using the “Community with a Shared Future” discourse as a case study, the purpose is to comparatively map the information landscape within the international and Chinese database systems. Design/methodology/approach A scientometric and comparative analysis was conducted on 1,502 publications from the Web of Science (WoS) and China National Knowledge Infrastructure (CNKI) databases (2013–2025). The approach uses knowledge mapping and network analysis to visualize the knowledge structure, identify core information sources through co-citation analysis and trace patterns of scholarly information diffusion. Findings The study reveals significant structural disparities in the knowledge organization of the topic. Information discovery pathways are highly divergent, producing structurally distinct knowledge clusters with limited cross-system citation overlap (WoS–CNKI co-citation rate < 5%). While core terminology (“mutual learning”) is shared, its semantic network differs significantly, impacting information retrieval and user understanding. The findings demonstrate how database architecture and regional focus shape the discovery and delivery of scholarly information. Originality/value This research provides a novel, data-driven comparison of two major global information systems, offering a theoretically grounded framework for analyzing the bifurcation of scholarly landscapes. It moves beyond a single-database study to reveal how database architectures and epistemic infrastructures shape the discovery and delivery of scholarly information, creating divergent understandings of the same global concept. For information professionals and librarians, the findings underscore the necessity of cross-database literacy and search strategies to achieve comprehensive information discovery. It also informs database designers about structural biases and opportunities for improving interoperability.