Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Анализ сетевой диффузии× | Двухмодальный сетевой анализ× | |
|---|---|---|
| Область | Сетевой анализ | Сетевой анализ |
| Семейство | Machine learning | Machine learning |
| Год появления≠ | 1927 (epidemic roots); network formalization 1990s–2000s | 1974 |
| Автор метода≠ | Kermack, W. O. & McKendrick, A. G. | Breiger, R. L. |
| Тип≠ | Simulation / analytical model | Bipartite graph analysis |
| Основополагающий источник≠ | Kermack, W. O. & McKendrick, A. G. (1927). A contribution to the mathematical theory of epidemics. Proceedings of the Royal Society of London A, 115(772), 700–721. DOI ↗ | Breiger, R. L. (1974). The duality of persons and groups. Social Forces, 53(2), 181–190. DOI ↗ |
| Другие названия | diffusion on networks, information diffusion, contagion spreading model, network propagation model | bipartite network analysis, affiliation network analysis, two-mode SNA, dual-projection network analysis |
| Связанные | 5 | 5 |
| Сводка≠ | Network diffusion analysis models how information, diseases, behaviors, or innovations spread across a graph of nodes and edges. Drawing on classical epidemic theory (SI, SIR, SIS) and modern network science, it tracks which nodes become infected, how quickly, and whether the spread reaches a global cascade or dies out locally. | 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. |
| ScholarGateНабор данных ↗ |
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