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| Relational Event Model× | Stochastic Actor-Oriented Model× | |
|---|---|---|
| Dziedzina | Sociology | Sociology |
| Rodzina≠ | Regression model | Machine learning |
| Rok powstania≠ | 2008 | 2001 |
| Twórca≠ | Carter T. Butts | Tom A. B. Snijders |
| Typ≠ | Event-history model for time-stamped relational events | Continuous-time model for longitudinal network and behavior dynamics |
| Źródło pierwotne≠ | Butts, C. T. (2008). A relational event framework for social action. Sociological Methodology, 38(1), 155–200. DOI ↗ | Snijders, T. A. B. (2001). The statistical evaluation of social network dynamics. Sociological Methodology, 31(1), 361–395. DOI ↗ |
| Inne nazwy | REM, relational event framework, dynamic network event model, event-history network model | SAOM, actor-based model, stochastic actor-based model, SIENA model |
| Pokrewne | 4 | 4 |
| Podsumowanie≠ | The relational event model (REM), introduced by Carter Butts in 2008, analyzes streams of time-stamped interactions — emails, radio calls, messages, citations — as a continuous-time event-history process. Rather than treating a network as a static set of ties, it models the instantaneous rate at which any sender directs an action at any receiver as a function of the history of past events, letting researchers test how prior interaction shapes future interaction. | The stochastic actor-oriented model (SAOM), implemented in the SIENA software, is a framework for analyzing the dynamics of social networks observed at two or more time points. It treats observed network panels as snapshots of an unobserved continuous-time process in which actors, at stochastically timed moments, evaluate their local network and decide whether to create, maintain, or drop a tie so as to improve their position according to an objective function. |
| ScholarGateZbiór danych ↗ |
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