2,667 research outputs found
Topics in social network analysis and network science
This chapter introduces statistical methods used in the analysis of social
networks and in the rapidly evolving parallel-field of network science.
Although several instances of social network analysis in health services
research have appeared recently, the majority involve only the most basic
methods and thus scratch the surface of what might be accomplished.
Cutting-edge methods using relevant examples and illustrations in health
services research are provided
Communities in Networks
We survey some of the concepts, methods, and applications of community
detection, which has become an increasingly important area of network science.
To help ease newcomers into the field, we provide a guide to available
methodology and open problems, and discuss why scientists from diverse
backgrounds are interested in these problems. As a running theme, we emphasize
the connections of community detection to problems in statistical physics and
computational optimization.Comment: survey/review article on community structure in networks; published
version is available at
http://people.maths.ox.ac.uk/~porterm/papers/comnotices.pd
Localization and Fluctuations in Quantum Kicked Rotors
We address the issue of fluctuations, about an exponential lineshape, in a
pair of one-dimensional kicked quantum systems exhibiting dynamical
localization. An exact renormalization scheme establishes the fractal character
of the fluctuations and provides a new method to compute the localization
length in terms of the fluctuations. In the case of a linear rotor, the
fluctuations are independent of the kicking parameter and exhibit
self-similarity for certain values of the quasienergy. For given , the
asymptotic localization length is a good characteristic of the localized
lineshapes for all quasienergies. This is in stark contrast to the quadratic
rotor, where the fluctuations depend upon the strength of the kicking and
exhibit local "resonances". These resonances result in strong deviations of the
localization length from the asymptotic value. The consequences are
particularly pronounced when considering the time evolution of a packet made up
of several quasienergy states.Comment: REVTEV Document. 9 pages, 4 figures submitted to PR
A Simple Generative Model of Collective Online Behaviour
Human activities increasingly take place in online environments, providing
novel opportunities for relating individual behaviours to population-level
outcomes. In this paper, we introduce a simple generative model for the
collective behaviour of millions of social networking site users who are
deciding between different software applications. Our model incorporates two
distinct components: one is associated with recent decisions of users, and the
other reflects the cumulative popularity of each application. Importantly,
although various combinations of the two mechanisms yield long-time behaviour
that is consistent with data, the only models that reproduce the observed
temporal dynamics are those that strongly emphasize the recent popularity of
applications over their cumulative popularity. This demonstrates---even when
using purely observational data without experimental design---that temporal
data-driven modelling can effectively distinguish between competing microscopic
mechanisms, allowing us to uncover new aspects of collective online behaviour.Comment: Updated, with new figures and Supplementary Informatio
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