901 research outputs found
Information Horizons in Networks
We investigate and quantify the interplay between topology and ability to
send specific signals in complex networks. We find that in a majority of
investigated real-world networks the ability to communicate is favored by the
network topology on small distances, but disfavored at larger distances. We
further discuss how the ability to locate specific nodes can be improved if
information associated to the overall traffic in the network is available.Comment: Submitted top PR
Small world yields the most effective information spreading
Spreading dynamics of information and diseases are usually analyzed by using
a unified framework and analogous models. In this paper, we propose a model to
emphasize the essential difference between information spreading and epidemic
spreading, where the memory effects, the social reinforcement and the
non-redundancy of contacts are taken into account. Under certain conditions,
the information spreads faster and broader in regular networks than in random
networks, which to some extent supports the recent experimental observation of
spreading in online society [D. Centola, Science {\bf 329}, 1194 (2010)]. At
the same time, simulation result indicates that the random networks tend to be
favorable for effective spreading when the network size increases. This
challenges the validity of the above-mentioned experiment for large-scale
systems. More significantly, we show that the spreading effectiveness can be
sharply enhanced by introducing a little randomness into the regular structure,
namely the small-world networks yield the most effective information spreading.
Our work provides insights to the understanding of the role of local clustering
in information spreading.Comment: 6 pages, 7 figures, accepted by New J. Phy
Asymptotic behavior of the Kleinberg model
We study Kleinberg navigation (the search of a target in a d-dimensional
lattice, where each site is connected to one other random site at distance r,
with probability proportional to r^{-a}) by means of an exact master equation
for the process. We show that the asymptotic scaling behavior for the delivery
time T to a target at distance L scales as (ln L)^2 when a=d, and otherwise as
L^x, with x=(d-a)/(d+1-a) for ad+1. These
values of x exceed the rigorous lower-bounds established by Kleinberg. We also
address the situation where there is a finite probability for the message to
get lost along its way and find short delivery times (conditioned upon arrival)
for a wide range of a's
Two-dimensional ranking of Wikipedia articles
The Library of Babel, described by Jorge Luis Borges, stores an enormous
amount of information. The Library exists {\it ab aeterno}. Wikipedia, a free
online encyclopaedia, becomes a modern analogue of such a Library. Information
retrieval and ranking of Wikipedia articles become the challenge of modern
society. While PageRank highlights very well known nodes with many ingoing
links, CheiRank highlights very communicative nodes with many outgoing links.
In this way the ranking becomes two-dimensional. Using CheiRank and PageRank we
analyze the properties of two-dimensional ranking of all Wikipedia English
articles and show that it gives their reliable classification with rich and
nontrivial features. Detailed studies are done for countries, universities,
personalities, physicists, chess players, Dow-Jones companies and other
categories.Comment: RevTex 9 pages, data, discussion added, more data at
http://www.quantware.ups-tlse.fr/QWLIB/2drankwikipedia
The Influence of Early Respondents: Information Cascade Effects in Online Event Scheduling
Sequential group decision-making processes, such as online event scheduling, can be subject to social influence if the decisions involve individuals’ subjective preferences and values. Indeed, prior work has shown that scheduling polls that allow respondents to see others’ answers are more likely to succeed than polls that hide other responses, suggesting the impact of social influence and coordination. In this paper, we investigate whether this difference is due to information cascade effects in which later respondents adopt the decisions of earlier respondents. Analyzing more than 1.3 million Doodle polls, we found evidence that cascading effects take place during event scheduling, and in particular, that early respondents have a larger influence on the outcome of a poll than people who come late. Drawing on simulations of an event scheduling model, we compare possible interventions to mitigate this bias and show that we can optimize the success of polls by hiding the responses of a small percentage of low availability respondents.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/134703/1/Romero et al 2017 (WSDM).pd
Thermodynamics of protein folding: a random matrix formulation
The process of protein folding from an unfolded state to a biologically
active, folded conformation is governed by many parameters e.g the sequence of
amino acids, intermolecular interactions, the solvent, temperature and chaperon
molecules. Our study, based on random matrix modeling of the interactions,
shows however that the evolution of the statistical measures e.g Gibbs free
energy, heat capacity, entropy is single parametric. The information can
explain the selection of specific folding pathways from an infinite number of
possible ways as well as other folding characteristics observed in computer
simulation studies.Comment: 21 Pages, no figure
The Cavity Approach to Parallel Dynamics of Ising Spins on a Graph
We use the cavity method to study parallel dynamics of disordered Ising
models on a graph. In particular, we derive a set of recursive equations in
single site probabilities of paths propagating along the edges of the graph.
These equations are analogous to the cavity equations for equilibrium models
and are exact on a tree. On graphs with exclusively directed edges we find an
exact expression for the stationary distribution of the spins. We present the
phase diagrams for an Ising model on an asymmetric Bethe lattice and for a
neural network with Hebbian interactions on an asymmetric scale-free graph. For
graphs with a nonzero fraction of symmetric edges the equations can be solved
for a finite number of time steps. Theoretical predictions are confirmed by
simulation results. Using a heuristic method, the cavity equations are extended
to a set of equations that determine the marginals of the stationary
distribution of Ising models on graphs with a nonzero fraction of symmetric
edges. The results of this method are discussed and compared with simulations
Cascading Dynamics in Modular Networks
In this paper we study a simple cascading process in a structured
heterogeneous population, namely, a network composed of two loosely coupled
communities. We demonstrate that under certain conditions the cascading
dynamics in such a network has a two--tiered structure that characterizes
activity spreading at different rates in the communities. We study the dynamics
of the model using both simulations and an analytical approach based on
annealed approximation, and obtain good agreement between the two. Our results
suggest that network modularity might have implications in various
applications, such as epidemiology and viral marketing.Comment: 5 pages, 4 figure
On the Mixing of Diffusing Particles
We study how the order of N independent random walks in one dimension evolves
with time. Our focus is statistical properties of the inversion number m,
defined as the number of pairs that are out of sort with respect to the initial
configuration. In the steady-state, the distribution of the inversion number is
Gaussian with the average ~N^2/4 and the standard deviation sigma N^{3/2}/6.
The survival probability, S_m(t), which measures the likelihood that the
inversion number remains below m until time t, decays algebraically in the
long-time limit, S_m t^{-beta_m}. Interestingly, there is a spectrum of
N(N-1)/2 distinct exponents beta_m(N). We also find that the kinetics of
first-passage in a circular cone provides a good approximation for these
exponents. When N is large, the first-passage exponents are a universal
function of a single scaling variable, beta_m(N)--> beta(z) with
z=(m-)/sigma. In the cone approximation, the scaling function is a root of a
transcendental equation involving the parabolic cylinder equation, D_{2
beta}(-z)=0, and surprisingly, numerical simulations show this prediction to be
exact.Comment: 9 pages, 6 figures, 2 table
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