Rethinking Thematic Evolution in Science Mapping: An Integrated Framework for Longitudinal Analysis
This work provides a more methodologically coherent and robust approach for researchers in science mapping to analyze the longitudinal evolution of scientific themes, addressing a structural inconsistency in existing methods.
This paper addresses the inconsistency in current science mapping methods for analyzing thematic evolution by proposing an integrated framework. It models thematic continuity through graded document affiliation and a lineage-strength measure, conceptualizing evolution as the reconfiguration of relational structures.
Strategic diagrams and co-word analysis are widely employed to examine the conceptual structure of scientific domains and their development over time. Yet a structural inconsistency characterises dominant longitudinal implementations: themes are detected through relational clustering in weighted networks, whereas their inter-temporal connections are commonly inferred from set-theoretic overlap among keywords or core documents. This study introduces a structurally integrated framework in which lineage reconstruction is embedded within the same weighted relational architecture that underpins cross-sectional detection. The approach models thematic continuity through graded document affiliation and a lineage-strength measure that combines directional coverage with centrality-weighted structural relevance, thereby conceptualising evolution as the reconfiguration of relational structures rather than simple lexical persistence. By aligning thematic detection and temporal modelling within a unified relational paradigm, the framework enhances the methodological coherence and interpretive robustness of longitudinal science mapping.