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| 二部ネットワーク分析× | Betweenness Centrality× | |
|---|---|---|
| 分野 | ネットワーク分析 | ネットワーク分析 |
| 系統 | Machine learning | Machine learning |
| 提唱年≠ | 1974 | 1977 |
| 提唱者≠ | Breiger, R. L. | Freeman, L. C. |
| 種類≠ | Bipartite graph analysis | Centrality measure |
| 原典≠ | Breiger, R. L. (1974). The duality of persons and groups. Social Forces, 53(2), 181–190. DOI ↗ | Freeman, L. C. (1977). A set of measures of centrality based on betweenness. Sociometry, 40(1), 35–41. DOI ↗ |
| 別名 | bipartite network analysis, affiliation network analysis, two-mode SNA, dual-projection network analysis | Freeman betweenness, BC, geodesic betweenness, shortest-path betweenness |
| 関連≠ | 5 | 6 |
| 概要≠ | Two-mode network analysis examines networks built from two distinct types of nodes — such as actors and events, authors and papers, or companies and board members — connected only across types. By analysing this bipartite structure directly or projecting it onto one-mode networks, researchers uncover affiliation patterns, shared memberships, and structural duality that are invisible in standard one-mode social network analysis. | Betweenness centrality, formalized by Linton C. Freeman in 1977, measures how often a node lies on the shortest path connecting every other pair of nodes in a network. High-betweenness nodes act as bridges or brokers: removing them fragments the network into disconnected components more severely than removing any other nodes. |
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