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| 다층 네트워크 분석× | 시간적 네트워크 분석× | |
|---|---|---|
| 분야 | 네트워크 분석 | 네트워크 분석 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | 2013–2014 (formal mathematical framework) | 2012 |
| 창시자≠ | Kivelä et al. (2014); De Domenico et al. (2013) | Holme & Saramäki (2012) — seminal framework |
| 유형≠ | Graph-theoretic network model | Dynamic graph analysis |
| 원전≠ | Kivelä, M. et al. (2014). Multilayer Networks. Journal of Complex Networks, 2(3), 203–271. DOI ↗ | Holme, P. & Saramäki, J. (2012). Temporal Networks. Physics Reports, 519(3), 97-125. DOI ↗ |
| 별칭 | multiplex network analysis, multiplex networks, Çok Katmanlı Ağ Analizi (Multiplex Networks) | dynamic network analysis, time-varying network analysis, Zamansal Ağ Analizi (Temporal / Dynamic Networks) |
| 관련≠ | 6 | 3 |
| 요약≠ | Multilayer network analysis is a graph-theoretic framework, formalised by Kivelä et al. (2014) and De Domenico et al. (2013), that represents the same set of nodes simultaneously across multiple relationship layers. Where a single-layer network collapses all relationships into one graph, the multilayer model preserves the distinct relational context of each layer — social platform, biological interaction type, or infrastructure tier — while also modelling how layers couple with each other through interlayer edges. | Temporal network analysis, formalised by Holme and Saramäki in their landmark 2012 Physics Reports survey, is the study of networks in which edges appear and disappear over time. Rather than collapsing all contacts into a single static graph, the approach preserves the precise timing of interactions — whether as contact sequences, time-stamped event lists, or windowed snapshots — and uses that timing to track how influence, disease, or information can actually propagate through the system. |
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