방법 비교
선택한 방법을 나란히 검토하세요. 서로 다른 행은 강조 표시됩니다.
| 이분 네트워크 분석× | 네트워크 모티프 분석× | |
|---|---|---|
| 분야 | 네트워크 분석 | 네트워크 분석 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | 1997 | 2002 |
| 창시자≠ | Borgatti & Everett (1997) formalised the two-mode network framework | — |
| 유형≠ | Graph-structural / relational analysis | Statistical pattern-detection method for directed graphs |
| 원전≠ | Borgatti, S.P. & Everett, M.G. (1997). Network Analysis of 2-Mode Data. Social Networks, 19(3), 243-269. link ↗ | Milo, R., Shen-Orr, S., Itzkovitz, S., Kashtan, N., Chklovskii, D., & Alon, U. (2002). Network Motifs: Simple Building Blocks of Complex Networks. Science, 298(5594), 824-827. DOI ↗ |
| 별칭 | two-mode network analysis, affiliation network analysis, İki Modlu Ağ Analizi (Bipartite Networks) | network motifs, subgraph significance profile, Ağ Motif Analizi (Network Motifs) |
| 관련≠ | 5 | 3 |
| 요약≠ | Bipartite network analysis, formalised by Borgatti and Everett in 1997, is a graph-structural method for studying networks in which nodes are divided into two disjoint sets — actors and events — and edges exist only between sets, never within them. It is the natural framework for author–paper, patient–disease, user–product, and any other affiliation data, and it extends one-mode network analysis by providing metrics and projection techniques tailored to the two-mode structure. | Network motif analysis is a statistical method for directed networks, introduced by Milo, Shen-Orr, and Alon in 2002, that identifies small recurring subgraph patterns — motifs — that appear significantly more often than would be expected in a comparable random network. By comparing a real network against a null ensemble of randomised graphs, the method reveals the elementary structural building blocks that define the functional organisation of biological regulatory networks, social networks, and other complex systems. |
| ScholarGate데이터셋 ↗ |
|
|