6 research outputs found
Modeling self-sustained activity cascades in socio-technical networks
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 time-evolution of cascades in a state-dependent
activity scenario.Comment: 5 pages, 3 figure
The Contagion Effects of Repeated Activation in Social Networks
Demonstrations, protests, riots, and shifts in public opinion respond to the
coordinating potential of communication networks. Digital technologies have
turned interpersonal networks into massive, pervasive structures that
constantly pulsate with information. Here, we propose a model that aims to
analyze the contagion dynamics that emerge in networks when repeated activation
is allowed, that is, when actors can engage recurrently in a collective effort.
We analyze how the structure of communication networks impacts on the ability
to coordinate actors, and we identify the conditions under which large-scale
coordination is more likely to emerge.Comment: Submitted for publicatio
Dynamical Systems on Networks: A Tutorial
We give a tutorial for the study of dynamical systems on networks. We focus
especially on "simple" situations that are tractable analytically, because they
can be very insightful and provide useful springboards for the study of more
complicated scenarios. We briefly motivate why examining dynamical systems on
networks is interesting and important, and we then give several fascinating
examples and discuss some theoretical results. We also briefly discuss
dynamical systems on dynamical (i.e., time-dependent) networks, overview
software implementations, and give an outlook on the field.Comment: 39 pages, 1 figure, submitted, more examples and discussion than
original version, some reorganization and also more pointers to interesting
direction