Generative models of simultaneously heavy-tailed distributions of interevent times on nodes and edges.

@article{FonsecadosReis2020GenerativeMO,
  title={Generative models of simultaneously heavy-tailed distributions of interevent times on nodes and edges.},
  author={Elohim Fonseca dos Reis and Aming Li and Naoki Masuda},
  journal={Physical review. E},
  year={2020},
  volume={102 5-1},
  pages={
          052303
        }
}
Intervals between discrete events representing human activities, as well as other types of events, often obey heavy-tailed distributions, and their impacts on collective dynamics on networks such as contagion processes have been intensively studied. The literature supports that such heavy-tailed distributions are present for interevent times associated with both individual nodes and individual edges in networks. However, the simultaneous presence of heavy-tailed distributions of interevent… Expand
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References

SHOWING 1-10 OF 112 REFERENCES
Long-tailed distributions of inter-event times as mixtures of exponential distributions
TLDR
This study introduces the minimum description length principle and shows that mixtures of exponential distributions with a few components are selected, as opposed to more complex mixtures in various datasets, and that the fitting accuracy is comparable to that of state-of-the-art algorithms to fit power-law distributions to data. Expand
Modeling temporal networks with bursty activity patterns of nodes and links
TLDR
This work introduces a temporal network model based on bursty node activation and shows that it leads to heavy-tailed inter-event time distributions for both node dynamics and link dynamics and indicates that activation processes intrinsic to nodes give rise to dynamical correlations across links. Expand
Voter model with non-Poissonian inter-event intervals
  • T. Takaguchi, N. Masuda
  • Mathematics, Computer Science
  • Physical review. E, Statistical, nonlinear, and soft matter physics
  • 2011
TLDR
This work uses a variant of the voter model and numerically compares the time to consensus of all the voters with different distributions of interevent intervals and different networks to investigate the effect of such a non-Poissonian nature of human behavior on dynamics of opinion formation. Expand
The origin of bursts and heavy tails in human dynamics
TLDR
It is shown that the bursty nature of human behaviour is a consequence of a decision-based queuing process: when individuals execute tasks based on some perceived priority, the timing of the tasks will be heavy tailed, with most tasks being rapidly executed, whereas a few experience very long waiting times. Expand
Modeling bursts and heavy tails in human dynamics
TLDR
It is shown that the bursty nature of human behavior is a consequence of a decision based queuing process: when individuals execute tasks based on some perceived priority, the timing of the tasks will be heavy tailed, most tasks being rapidly executed, while a few experiencing very long waiting times. Expand
Analytically Solvable Model of Spreading Dynamics with Non-Poissonian Processes
TLDR
An analytically solvable model of susceptible-infected spreading dynamics in infinite systems for arbitrary inter-event time distributions and for the whole time range shows that for early and intermediate times, the burstiness accelerates the spreading as compared to a Poisson-like process with the same mean and same lower bound of inter- event times. Expand
A Gillespie Algorithm for Non-Markovian Stochastic Processes
TLDR
The present study proposes an innovative Gillespie algorithm for renewal processes on the basis of the Laplace transform that allows renewal processes whose survival function of inter-event times is completely monotone functions and works faster than a recently proposed Gillespie algorithms for general renewal processes. Expand
Two-state Markov-chain Poisson nature of individual cellphone call statistics
TLDR
It is demonstrated that the individual call activities are driven by two independent Poisson processes, which can be combined within a minimal model in terms of a two-state first-order Markov chain giving very good agreement with the empirical distributions using the parameters estimated from real data for about half of the individuals in the authors' sample. Expand
A Poissonian explanation for heavy tails in e-mail communication
TLDR
It is demonstrated that the approximate power-law scaling of the inter-event time distribution is a consequence of circadian and weekly cycles of human activity, and a cascading nonhomogeneous Poisson process is proposed that explicitly integrates these periodic patterns in activity with an individual's tendency to continue participating in an activity. Expand
Impact of interactions on human dynamics
Queueing theory has been recently proposed as a framework to model the heavy tailed statistics of human activity patterns. The main predictions are the existence of a power-law distribution for theExpand
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