방법 비교

	이중 모드 네트워크 분석	모듈성 분석
분야	네트워크 분석	네트워크 분석
계열	Machine learning	Machine learning
기원 연도	1974	2004
창시자	Breiger, R. L.	Newman, M. E. J. & Girvan, M.
유형	Bipartite graph analysis	Community detection / graph partitioning
원전	Breiger, R. L. (1974). The duality of persons and groups. Social Forces, 53(2), 181–190.	Newman, M. E. J., & Girvan, M. (2004). Finding and evaluating community structure in networks. Physical Review E, 69(2), 026113.
별칭	bipartite network analysis, affiliation network analysis, two-mode SNA, dual-projection network analysis	Q-modularity, community structure detection, network modularity optimization, graph partitioning by modularity
관련	5	5
요약	Two-mode network analysis examines networks built from two distinct types of nodes — such as actors and events, authors and papers, or companies and board members — connected only across types. By analysing this bipartite structure directly or projecting it onto one-mode networks, researchers uncover affiliation patterns, shared memberships, and structural duality that are invisible in standard one-mode social network analysis.	Modularity analysis is a network science method, formalized by Newman and Girvan in 2004, that detects community structure in graphs by measuring whether edges are more concentrated within groups than expected by chance. Its scalar quality index Q guides algorithms that partition nodes into cohesive clusters, making it the most widely adopted framework for community detection in social, biological, and technological networks.