เปรียบเทียบวิธี

	การวิเคราะห์เครือข่ายหลายชั้นแบบถ่วงน้ำหนัก	Weighted Eigenvector Centrality
สาขาวิชา	การวิเคราะห์เครือข่าย	การวิเคราะห์เครือข่าย
ตระกูล	Machine learning	Machine learning
ปีกำเนิด	2014	1987 (binary); 2010 (weighted generalization)
ผู้ริเริ่ม	Battiston, F.; Kivela, M. et al.	Bonacich, P. (binary); Opsahl, T. et al. (weighted extension)
ประเภท	Network analysis framework	Spectral centrality measure
แหล่งต้นตำรับ	Battiston, F., Nicosia, V., & Latora, V. (2014). Structural measures for multiplex networks. Physical Review E, 89(3), 032804.	Bonacich, P. (1987). Power and centrality: A family of measures. American Journal of Sociology, 92(5), 1170–1182.
ชื่อเรียกอื่น	WMNA, weighted multilayer network analysis, weighted multi-relational network analysis, multiplex weighted graph analysis	WEC, weighted spectral centrality, strength-weighted eigenvector centrality, weighted eigenvector prestige
ที่เกี่ยวข้อง	5	6
สรุป	Weighted multiplex network analysis studies systems in which the same set of actors are connected through multiple types of relationships simultaneously, and each relationship carries a quantitative strength or frequency. By capturing both the variety and the intensity of ties across layers, it reveals patterns invisible to single-layer or unweighted network approaches.	Weighted eigenvector centrality extends the classic eigenvector centrality measure to graphs where edges carry numerical weights, scoring each node proportionally to the sum of its neighbors' scores multiplied by the connecting edge weights. Nodes score highly not just by having many connections but by being strongly linked to other influential nodes, making the measure sensitive to both tie strength and network position simultaneously.