7,829 research outputs found
Contagion processes on the static and activity driven coupling networks
The evolution of network structure and the spreading of epidemic are common
coexistent dynamical processes. In most cases, network structure is treated
either static or time-varying, supposing the whole network is observed in a
same time window. In this paper, we consider the epidemic spreading on a
network consisting of both static and time-varying structures. At meanwhile,
the time-varying part and the epidemic spreading are supposed to be of the same
time scale. We introduce a static and activity driven coupling (SADC) network
model to characterize the coupling between static (strong) structure and
dynamic (weak) structure. Epidemic thresholds of SIS and SIR model are studied
on SADC both analytically and numerically with various coupling strategies,
where the strong structure is of homogeneous or heterogeneous degree
distribution. Theoretical thresholds obtained from SADC model can both recover
and generalize the classical results in static and time-varying networks. It is
demonstrated that weak structures can make the epidemics break out much more
easily in homogeneous coupling but harder in heterogeneous coupling when
keeping same average degree in SADC networks. Furthermore, we show there exists
a threshold ratio of the weak structure to have substantive effects on the
breakout of the epidemics. This promotes our understanding of why epidemics can
still break out in some social networks even we restrict the flow of the
population
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
Can Network Theory-based Targeting Increase Technology Adoption?
In order to induce farmers to adopt a productive new agricultural technology,
we apply simple and complex contagion diffusion models on rich social network
data from 200 villages in Malawi to identify seed farmers to target and train
on the new technology. A randomized controlled trial compares these
theory-driven network targeting approaches to simpler strategies that either
rely on a government extension worker or an easily measurable proxy for the
social network (geographic distance between households) to identify seed
farmers. Our results indicate that technology diffusion is characterized by a
complex contagion learning environment in which most farmers need to learn from
multiple people before they adopt themselves. Network theory based targeting
can out-perform traditional approaches to extension, and we identify methods to
realize these gains at low cost to policymakers.
Keywords: Social Learning, Agricultural Technology Adoption, Complex
Contagion, Malawi
JEL Classification Codes: O16, O13Comment: 61 page
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
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