Articles producció científica> Enginyeria Informàtica i Matemàtiques

Evolving activity cascades on socio-technological networks

  • Dades identificatives

    Identificador: imarina:5133088
    Autors:
    Borge-Holthoefer, JavierPiedrahita, PabloArenas, Alex
    Resum:
    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.
  • Altres:

    Autor segons l'article: Borge-Holthoefer, Javier; Piedrahita, Pablo; Arenas, Alex;
    Departament: Enginyeria Informàtica i Matemàtiques
    Autor/s de la URV: Arenas Moreno, Alejandro
    Paraules clau: Threshold models Recurrent activity Complex networks
    Resum: 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.
    Àrees temàtiques: Transportation Social sciences, mathematical methods Artificial intelligence
    Accès a la llicència d'ús: https://creativecommons.org/licenses/by/3.0/es/
    Adreça de correu electrònic de l'autor: alexandre.arenas@urv.cat
    Identificador de l'autor: 0000-0003-0937-0334
    Data d'alta del registre: 2024-09-28
    Versió de l'article dipositat: info:eu-repo/semantics/acceptedVersion
    Enllaç font original: https://link.springer.com/article/10.1007/s42001-017-0012-7
    URL Document de llicència: https://repositori.urv.cat/ca/proteccio-de-dades/
    Referència a l'article segons font original: Journal Of Computational Social Science. 1 (1): 67-79
    Referència 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 de l'article: 10.1007/s42001-017-0012-7
    Entitat: Universitat Rovira i Virgili
    Any de publicació de la revista: 2018
    Tipus de publicació: Journal Publications
  • Paraules clau:

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