เปรียบเทียบวิธี

	ค่าศูนย์กลางเวกเตอร์ลักษณะเฉพาะแบบมีทิศทาง	การวิเคราะห์เครือข่ายสังคมแบบมีทิศทาง
สาขาวิชา	การวิเคราะห์เครือข่าย	การวิเคราะห์เครือข่าย
ตระกูล	Machine learning	Machine learning
ปีกำเนิด	1972–1987	1994
ผู้ริเริ่ม	Bonacich, P.	Wasserman, S. & Faust, K.
ประเภท	Centrality measure (eigenvector-based, directed)	Structural analysis of directed graphs
แหล่งต้นตำรับ	Bonacich, P. (1987). Power and centrality: A family of measures. American Journal of Sociology, 92(5), 1170–1182.	Wasserman, S. & Faust, K. (1994). Social Network Analysis: Methods and Applications. Cambridge University Press. ISBN: 978-0-521-38707-1
ชื่อเรียกอื่น	directed EC, asymmetric eigenvector centrality, right eigenvector centrality, left eigenvector centrality	directed SNA, digraph analysis, directed graph network analysis, asymmetric network analysis
ที่เกี่ยวข้อง	5	5
สรุป	Directed eigenvector centrality extends the classic eigenvector centrality to directed graphs by scoring each node according to the centrality of the nodes that point to it (in-direction) or that it points to (out-direction). A node earns a high score not merely by having many connections but by being connected to other highly central nodes, capturing asymmetric influence in citation networks, social hierarchies, and information flows.	Directed Social Network Analysis (directed SNA) studies networks in which every tie has an explicit direction — from a sender to a receiver — rather than treating relationships as symmetric. It extends the classical SNA toolkit with in-degree, out-degree, reciprocity, and asymmetric path measures, making it the appropriate framework wherever relationship direction carries substantive meaning, such as citation flows, advice-seeking, follower graphs, or information cascades.