K-core: A tool for detecting the conceptual structure of research fields. The practical case of Altmetrics
Abstract
In Social Network Analysis (SNA), the K-core decomposition is used for the detection of hierarchical layers in networks. The application of the K-core measure to a keyword network allows to represent the conceptual structure of a research field. The objective of this work was to propose the application of the K-core decomposition to show the evolution of the conceptual structure of the Altmetrics research field. The methodology was developed in six phases: data collection, keyword selection, elaboration of a keyword co-occurrence matrix, generation of a keyword network, K-core decomposition and visualization of the hierarchical structure. The result was the detection of five distinct layers. A central layer with basic and densely interconnected concepts, which formed the knowledge base of the field. An intermediate layer with mediating concepts, which showed the evolution of knowledge in the field. A lateral layer with concepts that indicated the specialization of the research field. A border layer with peripheral and isolated concepts, which represented the conceptual fronts in development. The conclusion was that the hierarchical decomposition of the keyword network achieved a deeper understanding of the conceptual structure, and the evolution, of the research field.
Keywords
Social Network Analysis, Keyword network, Community detection, K-core decomposition, AltmetricsReferences
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