24 research outputs found
Epidemic Threshold in Continuous-Time Evolving Networks
Current understanding of the critical outbreak condition on temporal networks
relies on approximations (time scale separation, discretization) that may bias
the results. We propose a theoretical framework to compute the epidemic
threshold in continuous time through the infection propagator approach. We
introduce the {\em weak commutation} condition allowing the interpretation of
annealed networks, activity-driven networks, and time scale separation into one
formalism. Our work provides a coherent connection between discrete and
continuous time representations applicable to realistic scenarios.Comment: 13 pages, 2 figure
Competition and dual users in complex contagion processes
We study the competition of two spreading entities, for example innovations,
in complex contagion processes in complex networks. We develop an analytical
framework and examine the role of dual users, i.e. agents using both
technologies. Searching for the spreading transition of the new innovation and
the extinction transition of a preexisting one, we identify different phases
depending on network mean degree, prevalence of preexisting technology, and
thresholds of the contagion process. Competition with the preexisting
technology effectively suppresses the spread of the new innovation, but it also
allows for phases of coexistence. The existence of dual users largely modifies
the transient dynamics creating new phases that promote the spread of a new
innovation and extinction of a preexisting one. It enables the global spread of
the new innovation even if the old one has the first-mover advantage.Comment: 9 pages, 4 figure
Competing contagion processes: Complex contagion triggered by simple contagion
Empirical evidence reveals that contagion processes often occur with
competition of simple and complex contagion, meaning that while some agents
follow simple contagion, others follow complex contagion. Simple contagion
refers to spreading processes induced by a single exposure to a contagious
entity while complex contagion demands multiple exposures for transmission.
Inspired by this observation, we propose a model of contagion dynamics with a
transmission probability that initiates a process of complex contagion. With
this probability nodes subject to simple contagion get adopted and trigger a
process of complex contagion. We obtain a phase diagram in the parameter space
of the transmission probability and the fraction of nodes subject to complex
contagion. Our contagion model exhibits a rich variety of phase transitions
such as continuous, discontinuous, and hybrid phase transitions, criticality,
tricriticality, and double transitions. In particular, we find a double phase
transition showing a continuous transition and a following discontinuous
transition in the density of adopted nodes with respect to the transmission
probability. We show that the double transition occurs with an intermediate
phase in which nodes following simple contagion become adopted but nodes with
complex contagion remain susceptible.Comment: 9 pages, 4 figure
Social contagions on interdependent lattice networks
Although an increasing amount of research is being done on the dynamical processes on interdependent spatial networks, knowledge of how interdependent spatial networks influence the dynamics of social contagion in them is sparse. Here we present a novel non-Markovian social contagion model on interdependent spatial networks composed of two identical two-dimensional lattices. We compare the dynamics of social contagion on networks with different fractions of dependency links and find that the density of final recovered nodes increases as the number of dependency links is increased. We use a finite-size analysis method to identify the type of phase transition in the giant connected components (GCC) of the final adopted nodes and find that as we increase the fraction of dependency links, the phase transition switches from second-order to first-order. In strong interdependent spatial networks with abundant dependency links, increasing the fraction of initial adopted nodes can induce the switch from a first-order to second-order phase transition associated with social contagion dynamics. In networks with a small number of dependency links, the phase transition remains second-order. In addition, both the second-order and first-order phase transition points can be decreased by increasing the fraction of dependency links or the number of initially-adopted nodes.This work was partially supported by National Natural Science Foundation of China (Grant Nos 61501358, 61673085), and the Fundamental Research Funds for the Central Universities. (61501358 - National Natural Science Foundation of China; 61673085 - National Natural Science Foundation of China; Fundamental Research Funds for the Central Universities)Published versio
Dynamics of organizational culture: Individual beliefs vs. social conformity
The complex nature of organizational culture challenges our ability to infers
its underlying dynamics from observational studies. Recent computational
studies have adopted a distinct different view, where plausible mechanisms are
proposed to describe a wide range of social phenomena, including the onset and
evolution of organizational culture. In this spirit, this work introduces an
empirically-grounded, agent-based model which relaxes a set of assumptions that
describes past work - (a) omittance of an individual's strive for achieving
cognitive coherence, (b) limited integration of important contextual factors -
by utilizing networks of beliefs and incorporating social rank into the
dynamics. As a result, we illustrate that: (i) an organization may appear to be
increasingly coherent in terms of organizational culture, yet be composed of
individuals with reduced levels of coherence, (ii) the components of social
conformity - peer-pressure and social rank - are influential at different
aggregation levels.Comment: 20 pages, 8 figure