방법 비교

	Directed Two-Mode Network Analysis	Directed Community Detection
분야	네트워크 분석	네트워크 분석
계열	Machine learning	Machine learning
기원 연도	1997	2008
창시자	Borgatti, S. P. & Everett, M. G.	Leicht, E. A. & Newman, M. E. J.; Rosvall, M. & Bergstrom, C. T.
유형	Structural network analysis	Graph partitioning / modularity optimization
원전	Wasserman, S. & Faust, K. (1994). Social Network Analysis: Methods and Applications (Ch. 8). Cambridge University Press. ISBN: 978-0-521-38707-1	Leicht, E. A. & Newman, M. E. J. (2008). Community structure in directed networks. Physical Review Letters, 100(11), 118703.
별칭	directed bipartite network analysis, asymmetric affiliation network analysis, directed actor-event network analysis, directed two-mode graph analysis	directed graph clustering, community detection in digraphs, directed modularity optimization, directed network partitioning
관련	6	6
요약	Directed two-mode network analysis studies bipartite graphs in which nodes belong to two distinct sets — such as actors and events, authors and papers, or firms and markets — and edges carry a direction, capturing asymmetric relationships like citation, referral, or endorsement. Combining the duality of two-mode structure with directed tie semantics reveals flow patterns and influence asymmetries that undirected or single-mode analyses would miss.	Directed community detection identifies densely interconnected groups of nodes in a directed network, accounting for the asymmetry of edges (e.g., A follows B does not imply B follows A). Adapting modularity or flow-based criteria to directed graphs reveals clusters that undirected methods systematically miss, making it essential for citation networks, follower graphs, and biological regulatory pathways.