BERTopic-based topic modeling in scientometric analysis of Blockchain integrated Digital Twin Security

This capsule contains the complete Python implementation used to reproduce the topic modeling and scientometric analysis reported in the associated IEEE Transactions on Systems, Man, and Cybernetics: Systems manuscript. The workflow applies an unsupervised BERTopic-based pipeline to Scopus bibliographic metadata to identify thematic structures and research trends in blockchain security. The capsule includes preprocessing scripts, embedding generation using a transformer-based language model, density-based clustering, and topic representation refinement through maximal marginal relevance. The bibliographic dataset used in the analysis is hosted on IEEE DataPort and is referenced within the capsule to ensure reproducibility without duplicating licensed data. The provided code enables transparent replication and extension of the reported results.