เปรียบเทียบวิธี

	การวิเคราะห์เครือข่ายสังคมแบบถ่วงน้ำหนัก	Weighted Betweenness Centrality
สาขาวิชา	การวิเคราะห์เครือข่าย	การวิเคราะห์เครือข่าย
ตระกูล	Machine learning	Machine learning
ปีกำเนิด	2004–2010	2010
ผู้ริเริ่ม	Barrat, A.; Opsahl, T. et al.	Opsahl, T.; Agneessens, F.; Skvoretz, J. (extending Freeman 1977 and Brandes 2001)
ประเภท	Network analysis framework	Centrality measure (path-based)
แหล่งต้นตำรับ	Barrat, A., Barthélemy, M., Pastor-Satorras, R., & Vespignani, A. (2004). The architecture of complex weighted networks. Proceedings of the National Academy of Sciences, 101(11), 3747–3752.	Opsahl, T., Agneessens, F., & Skvoretz, J. (2010). Node centrality in weighted networks: Generalizing degree and shortest paths. Social Networks, 32(3), 245–251.
ชื่อเรียกอื่น	Weighted SNA, valued network analysis, tie-strength network analysis, weighted graph analysis	WBC, weighted shortest-path betweenness, edge-weighted betweenness, geodesic betweenness (weighted)
ที่เกี่ยวข้อง	6	6
สรุป	Weighted Social Network Analysis extends classical SNA by assigning numeric values — weights — to ties between actors, capturing tie strength, interaction frequency, or resource flow. Rather than treating all connections as equal, it reveals who holds privileged positions by virtue of the intensity, not merely the existence, of their relationships.	Weighted Betweenness Centrality extends Freeman's betweenness measure to edge-weighted graphs by routing shortest paths through a tunable transformation of edge weights. Nodes that sit on many high-value shortest paths receive high scores, identifying brokers and bridges in social, biological, and information networks where tie strength matters.