Betweenness centrality of teams in social networks
| Autor: | Jongshin Lee, Soo Min Oh, Yongsun Lee, Byungnam Kahng |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Physics - Physics and Society
Hypergraph FOS: Physical sciences General Physics and Astronomy Binary number Physics and Society (physics.soc-ph) 01 natural sciences 010305 fluids & plasmas Social Networking Combinatorics Betweenness centrality 0103 physical sciences Humans 010306 general physics Condensed Matter - Statistical Mechanics Mathematical Physics Mathematics Statistical Mechanics (cond-mat.stat-mech) Social network Group (mathematics) business.industry Applied Mathematics Statistical and Nonlinear Physics Vertex (geometry) Bipartite graph Graph (abstract data type) business |
| Zdroj: | Chaos (Woodbury, N.Y.). 31(6) |
| ISSN: | 1089-7682 |
| Popis: | Betweenness centrality (BC) was proposed as an indicator of the extent of an individual's influence in a social network. It is measured by counting how many times a vertex (i.e., an individual) appears on all the shortest paths between pairs of vertices. A question naturally arises as to how the influence of a team or group in a social network can be measured. Here, we propose a method of measuring this influence on a bipartite graph comprising vertices (individuals) and hyperedges (teams). When the hyperedge size varies, the number of shortest paths between two vertices in a hypergraph can be larger than that in a binary graph. Thus, the power-law behavior of the team BC distribution breaks down in scale-free hypergraphs. However, when the weight of each hyperedge, for example, the performance per team member, is counted, the team BC distribution is found to exhibit power-law behavior. We find that a team with a widely connected member is highly influential. |
| Databáze: | OpenAIRE |
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