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Memory and burstiness in dynamic networks

Colman, E. and Vukadinovic Greetham, D. (2015) Memory and burstiness in dynamic networks. Physical Review E, 92 (1). 012817. ISSN 1539-3755

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To link to this item DOI: 10.1103/PhysRevE.92.012817

Abstract/Summary

A discrete-time random process is described, which can generate bursty sequences of events. A Bernoulli process, where the probability of an event occurring at time t is given by a fixed probability x, is modified to include a memory effect where the event probability is increased proportionally to the number of events that occurred within a given amount of time preceding t. For small values of x the interevent time distribution follows a power law with exponent −2−x. We consider a dynamic network where each node forms, and breaks connections according to this process. The value of x for each node depends on the fitness distribution, \rho(x), from which it is drawn; we find exact solutions for the expectation of the degree distribution for a variety of possible fitness distributions, and for both cases where the memory effect either is, or is not present. This work can potentially lead to methods to uncover hidden fitness distributions from fast changing, temporal network data, such as online social communications and fMRI scans.

Item Type:Article
Refereed:Yes
Divisions:Faculty of Science > School of Mathematical, Physical and Computational Sciences > Department of Mathematics and Statistics
Faculty of Science > School of Mathematical, Physical and Computational Sciences > Department of Mathematics and Statistics > Centre for the Mathematics of Human Behaviour (CMOHB)
ID Code:41429
Publisher:American Physical Society

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