74 research outputs found
Sustaining the Internet with Hyperbolic Mapping
The Internet infrastructure is severely stressed. Rapidly growing overheads
associated with the primary function of the Internet---routing information
packets between any two computers in the world---cause concerns among Internet
experts that the existing Internet routing architecture may not sustain even
another decade. Here we present a method to map the Internet to a hyperbolic
space. Guided with the constructed map, which we release with this paper,
Internet routing exhibits scaling properties close to theoretically best
possible, thus resolving serious scaling limitations that the Internet faces
today. Besides this immediate practical viability, our network mapping method
can provide a different perspective on the community structure in complex
networks
Statistical Laws Governing Fluctuations in Word Use from Word Birth to Word Death
We analyze the dynamic properties of 10^7 words recorded in English, Spanish
and Hebrew over the period 1800--2008 in order to gain insight into the
coevolution of language and culture. We report language independent patterns
useful as benchmarks for theoretical models of language evolution. A
significantly decreasing (increasing) trend in the birth (death) rate of words
indicates a recent shift in the selection laws governing word use. For new
words, we observe a peak in the growth-rate fluctuations around 40 years after
introduction, consistent with the typical entry time into standard dictionaries
and the human generational timescale. Pronounced changes in the dynamics of
language during periods of war shows that word correlations, occurring across
time and between words, are largely influenced by coevolutionary social,
technological, and political factors. We quantify cultural memory by analyzing
the long-term correlations in the use of individual words using detrended
fluctuation analysis.Comment: Version 1: 31 pages, 17 figures, 3 tables. Version 2 is streamlined,
eliminates substantial material and incorporates referee comments: 19 pages,
14 figures, 3 table
Languages cool as they expand: Allometric scaling and the decreasing need for new words
We analyze the occurrence frequencies of over 15 million words recorded in millions of books published during the past two centuries in seven different languages. For all languages and chronological subsets of the data we confirm that two scaling regimes characterize the word frequency distributions, with only the more common words obeying the classic Zipf law. Using corpora of unprecedented size, we test the allometric scaling relation between the corpus size and the vocabulary size of growing languages to demonstrate a decreasing marginal need for new words, a feature that is likely related to the underlying correlations between words. We calculate the annual growth fluctuations of word use which has a decreasing trend as the corpus size increases, indicating a slowdown in linguistic evolution following language expansion. This ââcooling patternââ forms the basis of a third statistical regularity, which unlike the Zipf and the Heaps law, is dynamical in nature
Impact of the Topology of Global Macroeconomic Network on the Spreading of Economic Crises
Throughout economic history, the global economy has experienced recurring crises. The persistent recurrence of such economic crises calls for an understanding of their generic features rather than treating them as singular events. The global economic system is a highly complex system and can best be viewed in terms of a network of interacting macroeconomic agents. In this regard, from the perspective of collective network dynamics, here we explore how the topology of the global macroeconomic network affects the patterns of spreading of economic crises. Using a simple toy model of crisis spreading, we demonstrate that an individual country's role in crisis spreading is not only dependent on its gross macroeconomic capacities, but also on its local and global connectivity profile in the context of the world economic network. We find that on one hand clustering of weak links at the regional scale can significantly aggravate the spread of crises, but on the other hand the current network structure at the global scale harbors higher tolerance of extreme crises compared to more âglobalizedâ random networks. These results suggest that there can be a potential hidden cost in the ongoing globalization movement towards establishing less-constrained, trans-regional economic links between countries, by increasing vulnerability of the global economic system to extreme crises
Identifying Hubs in Protein Interaction Networks
In spite of the scale-free degree distribution that characterizes most protein interaction networks (PINs), it is common to define an ad hoc degree scale that defines "hub" proteins having special topological and functional significance. This raises the concern that some conclusions on the functional significance of proteins based on network properties may not be robust.In this paper we present three objective methods to define hub proteins in PINs: one is a purely topological method and two others are based on gene expression and function. By applying these methods to four distinct PINs, we examine the extent of agreement among these methods and implications of these results on network construction.We find that the methods agree well for networks that contain a balance between error-free and unbiased interactions, indicating that the hub concept is meaningful for such networks
Evolution of scaling emergence in large-scale spatial epidemic spreading
Background: Zipf's law and Heaps' law are two representatives of the scaling
concepts, which play a significant role in the study of complexity science. The
coexistence of the Zipf's law and the Heaps' law motivates different
understandings on the dependence between these two scalings, which is still
hardly been clarified.
Methodology/Principal Findings: In this article, we observe an evolution
process of the scalings: the Zipf's law and the Heaps' law are naturally shaped
to coexist at the initial time, while the crossover comes with the emergence of
their inconsistency at the larger time before reaching a stable state, where
the Heaps' law still exists with the disappearance of strict Zipf's law. Such
findings are illustrated with a scenario of large-scale spatial epidemic
spreading, and the empirical results of pandemic disease support a universal
analysis of the relation between the two laws regardless of the biological
details of disease. Employing the United States(U.S.) domestic air
transportation and demographic data to construct a metapopulation model for
simulating the pandemic spread at the U.S. country level, we uncover that the
broad heterogeneity of the infrastructure plays a key role in the evolution of
scaling emergence.
Conclusions/Significance: The analyses of large-scale spatial epidemic
spreading help understand the temporal evolution of scalings, indicating the
coexistence of the Zipf's law and the Heaps' law depends on the collective
dynamics of epidemic processes, and the heterogeneity of epidemic spread
indicates the significance of performing targeted containment strategies at the
early time of a pandemic disease.Comment: 24pages, 7figures, accepted by PLoS ON
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