Confronta i metodi

	Analisi di Reti Small-World e Scale-Free	Analisi di Centralità
Campo	Analisi delle reti	Analisi delle reti
Famiglia	Process / pipeline	Process / pipeline
Anno di origine	1998 (small-world); 1999 (scale-free)	1979
Ideatore	—	Linton C. Freeman
Tipo	Descriptive / exploratory network analysis	Descriptive / exploratory network measure family
Fonte seminale	Watts, D.J. & Strogatz, S.H. (1998). Collective Dynamics of 'Small-World' Networks. Nature, 393(6684), 440-442.	Freeman, L.C. (1979). Centrality in Social Networks: Conceptual Clarification. Social Networks, 1(3), 215-239.
Alias	Küçük Dünya ve Ölçek-Bağımsız Ağ Analizi, small-world network, scale-free network, preferential attachment analysis	Merkeziyet Analizi (Degree, Betweenness, Eigenvector), node centrality, centrality measures, graph centrality
Correlati	9	5
Sintesi	Small-world and scale-free network analysis tests whether a real-world network exhibits two landmark topological signatures identified in 1998-1999: the Watts-Strogatz small-world property (high local clustering combined with short average path lengths) and the Barabási-Albert scale-free property (a degree distribution that follows a power law, meaning a small number of hubs connect to a disproportionately large share of other nodes). Together these frameworks transformed network science by showing that many social, biological, and technological networks share a common structural grammar.	Centrality analysis is a family of network-analytic measures, formalized by Freeman (1979), that quantifies the structural importance of individual nodes within a graph. Each centrality index captures a distinct mechanism of influence: degree centrality reflects direct connectivity, betweenness centrality identifies nodes that broker information flow, closeness centrality captures proximity to all others, and eigenvector centrality (along with PageRank) rewards connection to highly connected neighbors.