방법 비교

	Small-World and Scale-Free Network Analysis	중심성 분석
분야	네트워크 분석	네트워크 분석
계열	Process / pipeline	Process / pipeline
기원 연도	1998 (small-world); 1999 (scale-free)	1979
창시자	—	Linton C. Freeman
유형	Descriptive / exploratory network analysis	Descriptive / exploratory network measure family
원전	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.
별칭	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
관련	9	5
요약	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.