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Review Figure 3

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Figure 3: Summary of co-keyword analysis completed across the Full Corpus, and both Decades. Keyword co-occurrence matrices are visualized using graph theory methods, and modularity analytics applied to identify self-clustering networks (Panel A). To aid accessibility, these modules are visualized as colored concentric rings, each reflecting a module’s singular rank and theme (Psychological: Blue; Physiological: Red,[1] Panel B). Node size reflects normalized Eigenvector centrality, with prominent internal nodes labeled (see Supplementary Section 1 for full prominent node listing). Modular internal and external connectivity metrics were extracted, normalized and visualized relative to normalized corpus median values via a strategic diagram (Panel C). Providing a summary of internal connectivity along the Y-axis, this provides a measure of the cohesiveness of a thematic trend – with highly developed and interconnected themes reflected in higher levels of internal connectivity. Summative metrics on the X-axis provide an overview of external connectivity, demonstrating the central dominance of a theme to the research domain. The range of corpus internal and external connections display significant growth between Decade 1 and Decade 2, in line with research proliferation (see Figure 2), coupled with simultaneous constriction in modularity, perhaps indicative of the development of cohesive research themes (Figure 2 Panel D)—see Supplementary Table 4. For yearly (1994, 2006, 2015) assessment see Supplementary Figure 3.


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