Abstract Purpose Identifying technological opportunities in the field of sixth-generation mobile communications (6G) is crucial for research institutions and enterprises seeking to anticipate technological trajectories, and for policymakers formulating forward-looking innovation strategies. Design/methodology/approach Grounded in the notion that scientific knowledge drives technological R&D, this study integrates scientific publications and patent data to develop a framework for identifying technological opportunities in the 6G domain. We first employ a pretrained SBERT model to generate vector representations of mixed paper–patent data, followed by dimensionality reduction and visualization to characterize the structural features of science and technology. We then apply the HDBSCAN algorithm to identify thematic clusters across both corpora. Based on the clustering results and the semantic relationships between scientific themes and patented technologies, we construct two indicators – scientific knowledge reserve rate and technological invention competitiveness – to capture scientific and technological dynamics, respectively. A portfolio map is used to systematically identify potential technological opportunities within 6G. Findings The results demonstrate the feasibility and effectiveness of the proposed framework: eight potential technological opportunities are identified and validated to possess strong technological promise, confirming the robustness of our approach. Research limitations The analysis relies on scientific publications from WOS and patent data from DII, which may not fully capture the entire landscape of emerging 6G knowledge. Practical implications The framework provides actionable insights for 6G technology planning, enabling R&D institutions, enterprises, and policymakers to anticipate emerging trajectories and allocate innovation resources more effectively. Originality/value This study advances technology opportunity identification by bridging scientific research and technological development through semantic analysis. It offers a novel integrative framework that uncovers deep science–technology linkages and supports the cultivation of a global 6G innovation ecosystem and next-generation intelligent communication infrastructures.
Wang et al. (Mon,) studied this question.
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