手法を比較

	重み付き多重ネットワーク分析	重み付き固有ベクトル中心性
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	2014	1987 (binary); 2010 (weighted generalization)
提唱者	Battiston, F.; Kivela, M. et al.	Bonacich, P. (binary); Opsahl, T. et al. (weighted extension)
種類	Network analysis framework	Spectral centrality measure
原典	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.
別名	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
関連	5	6
概要	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.