השוואת שיטות
סקרו את השיטות שבחרתם זו לצד זו; שורות שבהן יש הבדל מודגשות.
| ניתוח רשתות רב-שכבתיות× | ניתוח רשתות זמניות× | |
|---|---|---|
| תחום | ניתוח רשתות | ניתוח רשתות |
| משפחה | Process / pipeline | Process / pipeline |
| שנת המקור≠ | 2013–2014 (formal mathematical framework) | 2012 |
| הוגה השיטה≠ | Kivelä et al. (2014); De Domenico et al. (2013) | Holme & Saramäki (2012) — seminal framework |
| סוג≠ | Graph-theoretic network model | Dynamic graph analysis |
| מקור מכונן≠ | 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 ↗ |
| כינויים | multiplex network analysis, multiplex networks, Çok Katmanlı Ağ Analizi (Multiplex Networks) | dynamic network analysis, time-varying network analysis, Zamansal Ağ Analizi (Temporal / Dynamic Networks) |
| קשורות≠ | 6 | 3 |
| תקציר≠ | 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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