Articles producció científica> Enginyeria Informàtica i Matemàtiques

Evolving activity cascades on socio-technological networks

  • Datos identificativos

    Identificador: imarina:5133088
    Autores:
    Borge-Holthoefer, JavierPiedrahita, PabloArenas, Alex
    Resumen:
    Networks are the substrate on which social contagion propagates, from the growth of social movements to the adoption of innovations. In the complex networks community, it took some time to realize the difference between simple propagation—e.g., the spread of disease—in which a single active node is sufficient to trigger the activation of its neighbors, and complex contagion, in which node activation requires simultaneous exposure to multiple active neighbors. Rooted in the social science literature, complex contagion has settled as the driving mechanism for behavior cascades on social networks. However, our access to digital traces of social interaction reveals, besides and beyond complex contagion, bursty activity patterns, repeated agent activation, and occasionally a form of synchronization under the form of trending topics and hypes. Thus, the threshold model—the paramount example in the tradition of complex contagion—needs to shift from a standpoint in which agents become irreversibly active (“one-off” events), to another in which agents continuously change their state and whose activity shows oscillating patterns. Here, we review a mechanistic model that, within the logic of complex contagion, accounts as well for the temporal evolution of behavior cascades. In it, agents follow the dynamics of integrate-and-fire oscillators. The affordances of the model—and of some recent variations on it—will open a discussion and outlook for future developments.
  • Otros:

    Autor según el artículo: Borge-Holthoefer, Javier; Piedrahita, Pablo; Arenas, Alex;
    Departamento: Enginyeria Informàtica i Matemàtiques
    Autor/es de la URV: Arenas Moreno, Alejandro
    Palabras clave: Threshold models Recurrent activity Complex networks
    Resumen: Networks are the substrate on which social contagion propagates, from the growth of social movements to the adoption of innovations. In the complex networks community, it took some time to realize the difference between simple propagation—e.g., the spread of disease—in which a single active node is sufficient to trigger the activation of its neighbors, and complex contagion, in which node activation requires simultaneous exposure to multiple active neighbors. Rooted in the social science literature, complex contagion has settled as the driving mechanism for behavior cascades on social networks. However, our access to digital traces of social interaction reveals, besides and beyond complex contagion, bursty activity patterns, repeated agent activation, and occasionally a form of synchronization under the form of trending topics and hypes. Thus, the threshold model—the paramount example in the tradition of complex contagion—needs to shift from a standpoint in which agents become irreversibly active (“one-off” events), to another in which agents continuously change their state and whose activity shows oscillating patterns. Here, we review a mechanistic model that, within the logic of complex contagion, accounts as well for the temporal evolution of behavior cascades. In it, agents follow the dynamics of integrate-and-fire oscillators. The affordances of the model—and of some recent variations on it—will open a discussion and outlook for future developments.
    Áreas temáticas: Transportation Social sciences, mathematical methods Artificial intelligence
    Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
    Direcció de correo del autor: alexandre.arenas@urv.cat
    Identificador del autor: 0000-0003-0937-0334
    Fecha de alta del registro: 2024-09-28
    Versión del articulo depositado: info:eu-repo/semantics/acceptedVersion
    Enlace a la fuente original: https://link.springer.com/article/10.1007/s42001-017-0012-7
    URL Documento de licencia: https://repositori.urv.cat/ca/proteccio-de-dades/
    Referencia al articulo segun fuente origial: Journal Of Computational Social Science. 1 (1): 67-79
    Referencia de l'ítem segons les normes APA: Borge-Holthoefer, Javier; Piedrahita, Pablo; Arenas, Alex; (2018). Evolving activity cascades on socio-technological networks. Journal Of Computational Social Science, 1(1), 67-79. DOI: 10.1007/s42001-017-0012-7
    DOI del artículo: 10.1007/s42001-017-0012-7
    Entidad: Universitat Rovira i Virgili
    Año de publicación de la revista: 2018
    Tipo de publicación: Journal Publications
  • Palabras clave:

    Artificial Intelligence,Social Sciences, Mathematical Methods,Transportation
    Threshold models
    Recurrent activity
    Complex networks
    Transportation
    Social sciences, mathematical methods
    Artificial intelligence
  • Documentos:

  • Cerca a google

    Search to google scholar