The distribution of citations received by scientific publications can be approximated by a power law, a finding that has been explained by “cumulative advantage”. This paper argues that socially embedded learning is a plausible mechanism behind this cumulative advantage. A model assuming that scientists face a time trade-off between learning and writing papers, that they learn the papers known ...

Based on empirical financial time-series, we show that the ”silence-breaking” probability follows a super-universal power law: the probability of observing a large movement is inversely proportional to the length of the ongoing low-variability period. Such a scaling law has been previously predicted theoretically [1], assuming that the length-distribution of the low-variability periods follows ...

Many growth models have been published to model the behavior of real complex networks. These models are able to reproduce several of the topological properties of such networks. However, in most of these growth models, the number of outgoing links (i.e., out-degree) of nodes added to the network is constant, that is all nodes in the network are born with the same number of outgoing links. In ot...

This paper examines the distribution of areas burned in forest fires. Empirical size distributions, derived from extensive fire records, for six regions in North America are presented. While they show some commonalities, it appears that a simple power-law distribution of sizes, as has been suggested by some authors, is too simple to describe the distributions over their full range. A stochastic...

The one-dimensional (1D) power law velocity distribution, commonly used for computing velocities in open channel flow, has been derived empirically. However, a multitude of problems, such as scour around bridge piers, cutoffs and diversions, pollutant dispersion, and so on, require the velocity distribution in two dimensions. This paper employs the Shannon entropy theory for deriving the power ...

On-line communities offer a great opportunity to investigate human dynamics, because much information about individuals is registered in databases. In this paper, based on data statistics of online comments on Blog posts, we first present an empirical study of a comment arrival-time interval distribution. We find that people interested in some subjects gradually disappear and the interval distr...

Scale-free networks arise from power-law degree distributions. Due to the finite size of real-world networks, the power law inevitably has a cutoff at some maximum degree ∆. We investigate the relative size of the giant component S in the large-network limit. We show that S as a function of ∆ increases fast when ∆ is just large enough for the giant component to exist, but increases ever more sl...

We propose a growing network model for a community with a group structure. The community consists of individual members and groups, gatherings of members. The community grows as a new member is introduced by an existing member at each time step. The new member then creates a new group or joins one of the groups of the introducer. We investigate the emerging community structure analytically and ...

We investigate the waiting-time distribution of the absolute return in the Korean stock-market index KOSPI. We define the waiting time as a time interval during which the normalized absolute return remains continuously below a threshold rc. Through an exponential bin plot, we observe that the waiting-time distribution shows power-law behavior, pf (t) ∼ t−β , for a range of threshold values. The...

The resource distribution and peer links in P2P network have an obvious scale free character follows power law distribution. Using this inherent character of P2P network to design resource search strategy is great significant for improving the search efficiency and reducing the costs. We analyze the scale free character in P2P network, and propose the reliable random walk search algorithm which...