Abstract
The ability to understand and eventually predict the emergence of information and activation cascades in social networks is core to complex socio-technical systems research. However, the complexity of social interactions makes this a challenging enterprise. Previous works on cascade models assume that the emergence of this collective phenomenon is related to the activity observed in the local neighborhood of individuals, but do not consider what determines the willingness to spread information in a time-varying process. Here we present a mechanistic model that accounts for the temporal evolution of the individual state in a simplified setup. We model the activity of the individuals as a complex network of interacting integrate-and-fire oscillators. The model reproduces the statistical characteristics of the cascades in real systems, and provides a framework to study the time evolution of cascades in a state-dependent activity scenario.
| Original language | English |
|---|---|
| Article number | 48004 |
| Journal | EPL |
| Volume | 104 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 1 Nov 2013 |
| Externally published | Yes |
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ASJC Scopus subject areas
- Physics and Astronomy(all)
Cite this
Modeling self-sustained activity cascades in socio-technical networks. / Piedrahita, P.; Borge-Holthoefer, J.; Moreno, Y.; Arenas, A.
In: EPL, Vol. 104, No. 4, 48004, 01.11.2013.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Modeling self-sustained activity cascades in socio-technical networks
AU - Piedrahita, P.
AU - Borge-Holthoefer, J.
AU - Moreno, Y.
AU - Arenas, A.
PY - 2013/11/1
Y1 - 2013/11/1
N2 - The ability to understand and eventually predict the emergence of information and activation cascades in social networks is core to complex socio-technical systems research. However, the complexity of social interactions makes this a challenging enterprise. Previous works on cascade models assume that the emergence of this collective phenomenon is related to the activity observed in the local neighborhood of individuals, but do not consider what determines the willingness to spread information in a time-varying process. Here we present a mechanistic model that accounts for the temporal evolution of the individual state in a simplified setup. We model the activity of the individuals as a complex network of interacting integrate-and-fire oscillators. The model reproduces the statistical characteristics of the cascades in real systems, and provides a framework to study the time evolution of cascades in a state-dependent activity scenario.
AB - The ability to understand and eventually predict the emergence of information and activation cascades in social networks is core to complex socio-technical systems research. However, the complexity of social interactions makes this a challenging enterprise. Previous works on cascade models assume that the emergence of this collective phenomenon is related to the activity observed in the local neighborhood of individuals, but do not consider what determines the willingness to spread information in a time-varying process. Here we present a mechanistic model that accounts for the temporal evolution of the individual state in a simplified setup. We model the activity of the individuals as a complex network of interacting integrate-and-fire oscillators. The model reproduces the statistical characteristics of the cascades in real systems, and provides a framework to study the time evolution of cascades in a state-dependent activity scenario.
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U2 - 10.1209/0295-5075/104/48004
DO - 10.1209/0295-5075/104/48004
M3 - Article
AN - SCOPUS:84890759967
VL - 104
JO - EPL
JF - EPL
SN - 0295-5075
IS - 4
M1 - 48004
ER -