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原文連結
論文資訊
- 類型：已發表論文
- 日期：2022-10-25
摘要
Centrality, in some sense, captures the extent to which a vertex controls the flow of 資訊 in a 網絡. Here, we propose Local Detour Centrality as a novel centrality-based betweenness measure that captures the extent to which a vertex shortens paths between neighboring vertices as compared to alternative paths. After presenting our measure, we demonstrate empirically that it differs from other leading central measures, such as betweenness, degree, closeness, and the number of triangles. Through an empirical case study, we provide a possible interpretation for Local Detour Centrality as a measure that captures the extent to which a word is characterized by contextual 多樣性 within a semantic 網絡. We then examine the relationship between our measure and the accessibility to knowledge stored in memory
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