7,035 research outputs found
Cross-over behaviour in a communication network
We address the problem of message transfer in a communication network. The
network consists of nodes and links, with the nodes lying on a two dimensional
lattice. Each node has connections with its nearest neighbours, whereas some
special nodes, which are designated as hubs, have connections to all the sites
within a certain area of influence. The degree distribution for this network is
bimodal in nature and has finite variance. The distribution of travel times
between two sites situated at a fixed distance on this lattice shows fat
fractal behaviour as a function of hub-density. If extra assortative
connections are now introduced between the hubs so that each hub is connected
to two or three other hubs, the distribution crosses over to power-law
behaviour. Cross-over behaviour is also seen if end-to-end short cuts are
introduced between hubs whose areas of influence overlap, but this is much
milder in nature. In yet another information transmission process, namely, the
spread of infection on the network with assortative connections, we again
observed cross-over behaviour of another type, viz. from one power-law to
another for the threshold values of disease transmission probability. Our
results are relevant for the understanding of the role of network topology in
information spread processes.Comment: 12 figure
Epidemic Thresholds with External Agents
We study the effect of external infection sources on phase transitions in
epidemic processes. In particular, we consider an epidemic spreading on a
network via the SIS/SIR dynamics, which in addition is aided by external agents
- sources unconstrained by the graph, but possessing a limited infection rate
or virulence. Such a model captures many existing models of externally aided
epidemics, and finds use in many settings - epidemiology, marketing and
advertising, network robustness, etc. We provide a detailed characterization of
the impact of external agents on epidemic thresholds. In particular, for the
SIS model, we show that any external infection strategy with constant virulence
either fails to significantly affect the lifetime of an epidemic, or at best,
sustains the epidemic for a lifetime which is polynomial in the number of
nodes. On the other hand, a random external-infection strategy, with rate
increasing linearly in the number of infected nodes, succeeds under some
conditions to sustain an exponential epidemic lifetime. We obtain similar sharp
thresholds for the SIR model, and discuss the relevance of our results in a
variety of settings.Comment: 12 pages, 2 figures (to appear in INFOCOM 2014
State of the art 2015: a literature review of social media intelligence capabilities for counter-terrorism
Overview
This paper is a review of how information and insight can be drawn from open social media sources. It focuses on the specific research techniques that have emerged, the capabilities they provide, the possible insights they offer, and the ethical and legal questions they raise. These techniques are considered relevant and valuable in so far as they can help to maintain public safety by preventing terrorism, preparing for it, protecting the public from it and pursuing its perpetrators. The report also considers how far this can be achieved against the backdrop of radically changing technology and public attitudes towards surveillance. This is an updated version of a 2013 report paper on the same subject, State of the Art. Since 2013, there have been significant changes in social media, how it is used by terrorist groups, and the methods being developed to make sense of it.
The paper is structured as follows:
Part 1 is an overview of social media use, focused on how it is used by groups of interest to those involved in counter-terrorism. This includes new sections on trends of social media platforms; and a new section on Islamic State (IS).
Part 2 provides an introduction to the key approaches of social media intelligence (henceforth âSOCMINTâ) for counter-terrorism.
Part 3 sets out a series of SOCMINT techniques. For each technique a series of capabilities and insights are considered, the validity and reliability of the method is considered, and how they might be applied to counter-terrorism work explored.
Part 4 outlines a number of important legal, ethical and practical considerations when undertaking SOCMINT work
Phase transition for the Maki-Thompson rumour model on a small-world network
We consider the Maki-Thompson model for the stochastic propagation of a
rumour within a population. We extend the original hypothesis of homogenously
mixed population by allowing for a small-world network embedding the model.
This structure is realized starting from a -regular ring and by inserting,
in the average, additional links in such a way that and are
tuneable parameter for the population architecture. We prove that this system
exhibits a transition between regimes of localization (where the final number
of stiflers is at most logarithmic in the population size) and propagation
(where the final number of stiflers grows algebraically with the population
size) at a finite value of the network parameter . A quantitative estimate
for the critical value of is obtained via extensive numerical simulations.Comment: 24 pages, 4 figure
Weighted distances in scale-free configuration models
In this paper we study first-passage percolation in the configuration model
with empirical degree distribution that follows a power-law with exponent . We assign independent and identically distributed (i.i.d.)\ weights
to the edges of the graph. We investigate the weighted distance (the length of
the shortest weighted path) between two uniformly chosen vertices, called
typical distances. When the underlying age-dependent branching process
approximating the local neighborhoods of vertices is found to produce
infinitely many individuals in finite time -- called explosive branching
process -- Baroni, Hofstad and the second author showed that typical distances
converge in distribution to a bounded random variable. The order of magnitude
of typical distances remained open for the case when the
underlying branching process is not explosive. We close this gap by determining
the first order of magnitude of typical distances in this regime for arbitrary,
not necessary continuous edge-weight distributions that produce a non-explosive
age-dependent branching process with infinite mean power-law offspring
distributions. This sequence tends to infinity with the amount of vertices,
and, by choosing an appropriate weight distribution, can be tuned to be any
growing function that is , where is the number of vertices
in the graph. We show that the result remains valid for the the erased
configuration model as well, where we delete loops and any second and further
edges between two vertices.Comment: 24 page
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