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Rumana Lakdawala1, Joris Mulder1, Roger Leenders2,3

  • 1Department of Methodology and Statistics, Tilburg School of Social and Behavioral Sciences, Tilburg University, Tilburg, The Netherlands.

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|August 27, 2025
PubMed
Resumen
Este resumen es generado por máquina.

Este estudio introduce marcos estadísticos y un paquete R (remulate) para simular redes de eventos relacionales. Esto permite una mejor comprensión de la dinámica de la interacción social y ayuda en los desafíos de análisis de redes.

Palabras clave:
Modelos orientados al actorModelos de interacción diádicaLas intervencionesEvaluación de la adecuación del modeloEventos relacionadosTécnicas de simulaciónLas redes sociales temporales

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Área de la Ciencia:

  • Análisis de las redes sociales
  • Ciencias sociales computacionales
  • Modelado estadístico

Sus antecedentes:

  • Los fenómenos sociales a menudo implican interacciones repetidas a lo largo del tiempo, lo que requiere métodos para analizar estas dinámicas.
  • La comprensión de los mecanismos de interacción social requiere técnicas de simulación estadística para los datos de la red temporal de grano fino.

Objetivo del estudio:

  • Presentar marcos estadísticos para la simulación de redes de eventos relacionales utilizando modelos diádicos y orientados a los actores.
  • Demostrar la utilidad de la simulación para abordar los desafíos clave en el análisis temporal de las redes sociales.
  • Introducir el paquete R "remulate" para la implementación de estos marcos de simulación.

Principales métodos:

  • Desarrollo de marcos estadísticos para modelos de eventos relacionales.
  • Implementación de estos marcos en el paquete R "remulate".
  • Aplicación de técnicas de simulación a través de cinco estudios de caso diferentes.

Principales resultados:

  • El paquete "remulate" proporciona herramientas para simular redes de eventos relacionales.
  • La simulación ayuda en la evaluación del modelo, el desarrollo de la teoría social (por ejemplo, la distinción óptima) y la comprensión de los efectos de la intervención.
  • El análisis basado en la simulación mejora la evaluación de la sensibilidad del modelo y la predicción de la dinámica relacional futura.

Conclusiones:

  • El marco de simulación presentado y el paquete "remulate" son herramientas valiosas para los investigadores.
  • Estas herramientas facilitan una comprensión más profunda de la dinámica de la interacción social a partir de datos de eventos relacionales de la vida real.
  • La simulación es crucial para avanzar en el análisis temporal de las redes sociales.