Σύγκριση μεθόδων

	Ανάλυση Κατευθυνόμενων Κοινωνικών Δικτύων	Κεντρικότητα Βαθμού
Πεδίο	Ανάλυση Δικτύων	Ανάλυση Δικτύων
Οικογένεια	Machine learning	Machine learning
Έτος προέλευσης	1994	1978
Δημιουργός	Wasserman, S. & Faust, K.	Freeman, L. C.
Τύπος	Structural analysis of directed graphs	Node-level centrality measure
Θεμελιώδης πηγή	Wasserman, S. & Faust, K. (1994). Social Network Analysis: Methods and Applications. Cambridge University Press. ISBN: 978-0-521-38707-1	Freeman, L. C. (1978). Centrality in social networks: Conceptual clarification. Social Networks, 1(3), 215–239.
Εναλλακτικές ονομασίες	directed SNA, digraph analysis, directed graph network analysis, asymmetric network analysis	node degree, degree score, DC, connectivity centrality
Συναφείς	5	6
Σύνοψη	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.	Degree centrality is the simplest and most intuitive measure of a node's importance in a network, defined as the number of direct ties a node has to other nodes. Normalized by dividing by the maximum possible ties, it allows comparison across networks of different sizes and is the starting point of almost every network analysis.