1,077 research outputs found
Opinion formation driven by PageRank node influence on directed networks
We study a two states opinion formation model driven by PageRank node
influence and report an extensive numerical study on how PageRank affects
collective opinion formations in large-scale empirical directed networks. In
our model the opinion of a node can be updated by the sum of its neighbor
nodes' opinions weighted by the node influence of the neighbor nodes at each
step. We consider PageRank probability and its sublinear power as node
influence measures and investigate evolution of opinion under various
conditions. First, we observe that all networks reach steady state opinion
after a certain relaxation time. This time scale is decreasing with the
heterogeneity of node influence in the networks. Second, we find that our model
shows consensus and non-consensus behavior in steady state depending on types
of networks: Web graph, citation network of physics articles, and LiveJournal
social network show non-consensus behavior while Wikipedia article network
shows consensus behavior. Third, we find that a more heterogeneous influence
distribution leads to a more uniform opinion state in the cases of Web graph,
Wikipedia, and Livejournal. However, the opposite behavior is observed in the
citation network. Finally we identify that a small number of influential nodes
can impose their own opinion on significant fraction of other nodes in all
considered networks. Our study shows that the effects of heterogeneity of node
influence on opinion formation can be significant and suggests further
investigations on the interplay between node influence and collective opinion
in networks.Comment: 10 pages, 6 figures. Published in Physica A 436, 707-715 (2015
Highlighting Entanglement of Cultures via Ranking of Multilingual Wikipedia Articles
How different cultures evaluate a person? Is an important person in one
culture is also important in the other culture? We address these questions via
ranking of multilingual Wikipedia articles. With three ranking algorithms based
on network structure of Wikipedia, we assign ranking to all articles in 9
multilingual editions of Wikipedia and investigate general ranking structure of
PageRank, CheiRank and 2DRank. In particular, we focus on articles related to
persons, identify top 30 persons for each rank among different editions and
analyze distinctions of their distributions over activity fields such as
politics, art, science, religion, sport for each edition. We find that local
heroes are dominant but also global heroes exist and create an effective
network representing entanglement of cultures. The Google matrix analysis of
network of cultures shows signs of the Zipf law distribution. This approach
allows to examine diversity and shared characteristics of knowledge
organization between cultures. The developed computational, data driven
approach highlights cultural interconnections in a new perspective.Comment: Published in PLoS ONE
(http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0074554).
Supporting information is available on the same webpag
Concurrent enhancement of percolation and synchronization in adaptive networks
Co-evolutionary adaptive mechanisms are not only ubiquitous in nature, but
also beneficial for the functioning of a variety of systems. We here consider
an adaptive network of oscillators with a stochastic, fitness-based, rule of
connectivity, and show that it self-organizes from fragmented and incoherent
states to connected and synchronized ones. The synchronization and percolation
are associated to abrupt transitions, and they are concurrently (and
significantly) enhanced as compared to the non-adaptive case. Finally we
provide evidence that only partial adaptation is sufficient to determine these
enhancements. Our study, therefore, indicates that inclusion of simple adaptive
mechanisms can efficiently describe some emergent features of networked
systems' collective behaviors, and suggests also self-organized ways to control
synchronization and percolation in natural and social systems.Comment: Published in Scientific Report
Google matrix of the citation network of Physical Review
We study the statistical properties of spectrum and eigenstates of the Google
matrix of the citation network of Physical Review for the period 1893 - 2009.
The main fraction of complex eigenvalues with largest modulus is determined
numerically by different methods based on high precision computations with up
to binary digits that allows to resolve hard numerical problems for
small eigenvalues. The nearly nilpotent matrix structure allows to obtain a
semi-analytical computation of eigenvalues. We find that the spectrum is
characterized by the fractal Weyl law with a fractal dimension .
It is found that the majority of eigenvectors are located in a localized phase.
The statistical distribution of articles in the PageRank-CheiRank plane is
established providing a better understanding of information flows on the
network. The concept of ImpactRank is proposed to determine an influence domain
of a given article. We also discuss the properties of random matrix models of
Perron-Frobenius operators.Comment: 25 pages. 17 figures. Published in Phys. Rev.
A Compact MultiBand and Dual-Polarized Mobile Base-Station Antenna Using Optimal Array Structure
This paper introduces a multiband base-station antenna to provide multiple communications services. There is growing need for multiband base-station antennas for mobile communications to serve existing 2nd and 3rd generation systems and to provide emerging 4th generation communication service as well as WiFi. For example, cellular, PCS, and especially WCDMA service are currently widely used in Korea, and 4th generation service (WiBro and LTE), introduced in 2011, will have to operate in parallel with existing services. The proposed multiband base-station antenna can provide a single/dual/triple or more multiple services using dual-polarization (±45° linear polarizations) according to the requirements of the service provider. This antenna has a shared aperture, having several array antenna sets for multiple services (Band 1: cellular service in 0.824~0.894 GHz, Band 2: PCS, WCDMA, and WiFi in 1.920~2.170 GHz, Band 3: WiBro and WiMAX in 2.300~2.400 GHz, and Band 4: WiMAX in 5.150~5.850 GHz). This antenna can be helpful for reducing base-station operating expenses and to create a clean urban landscape by minimizing the number of base-station antennas, which are increasing rapidly
Empirical analysis of congestion spreading in Seoul traffic network
Understanding how local traffic congestion spreads in urban traffic networks
is fundamental to solving congestion problems in cities. In this work, by
analyzing the high resolution data of traffic velocity in Seoul, we empirically
investigate the spreading patterns and cluster formation of traffic congestion
in a real-world urban traffic network. To do this, we propose a congestion
identification method suitable for various types of interacting traffic flows
in urban traffic networks. Our method reveals that congestion spreading in
Seoul may be characterized by a tree-like structure during the morning rush
hour but a more persistent loop structure during the evening rush hour. Our
findings suggest that diffusion and stacking processes of local congestion play
a major role in the formation of urban traffic congestion.Comment: 10 pages, 7 figure
Tail-scope: Using friends to estimate heavy tails of degree distributions in large-scale complex networks
Many complex networks in natural and social phenomena have often been
characterized by heavy-tailed degree distributions. However, due to rapidly
growing size of network data and concerns on privacy issues about using these
data, it becomes more difficult to analyze complete data sets. Thus, it is
crucial to devise effective and efficient estimation methods for heavy tails of
degree distributions in large-scale networks only using local information of a
small fraction of sampled nodes. Here we propose a tail-scope method based on
local observational bias of the friendship paradox. We show that the tail-scope
method outperforms the uniform node sampling for estimating heavy tails of
degree distributions, while the opposite tendency is observed in the range of
small degrees. In order to take advantages of both sampling methods, we devise
the hybrid method that successfully recovers the whole range of degree
distributions. Our tail-scope method shows how structural heterogeneities of
large-scale complex networks can be used to effectively reveal the network
structure only with limited local information.Comment: 9 pages, 6 figure
Interactions of cultures and top people of Wikipedia from ranking of 24 language editions
Wikipedia is a huge global repository of human knowledge, that can be
leveraged to investigate interwinements between cultures. With this aim, we
apply methods of Markov chains and Google matrix, for the analysis of the
hyperlink networks of 24 Wikipedia language editions, and rank all their
articles by PageRank, 2DRank and CheiRank algorithms. Using automatic
extraction of people names, we obtain the top 100 historical figures, for each
edition and for each algorithm. We investigate their spatial, temporal, and
gender distributions in dependence of their cultural origins. Our study
demonstrates not only the existence of skewness with local figures, mainly
recognized only in their own cultures, but also the existence of global
historical figures appearing in a large number of editions. By determining the
birth time and place of these persons, we perform an analysis of the evolution
of such figures through 35 centuries of human history for each language, thus
recovering interactions and entanglement of cultures over time. We also obtain
the distributions of historical figures over world countries, highlighting
geographical aspects of cross-cultural links. Considering historical figures
who appear in multiple editions as interactions between cultures, we construct
a network of cultures and identify the most influential cultures according to
this network.Comment: 32 pages. 10 figures. Submitted for publication. Supporting
information is available on
http://www.quantware.ups-tlse.fr/QWLIB/topwikipeople
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