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General Centrality in a hypergraph

The goal of this paper is to present a centrality measurement for the nodes of a hypergraph, by using existing literature which extends eigenvector centrality from a graph to a hypergraph, and literature which give a general centrality measurement for a graph. We will use this measurement to say more about the number of communications in a hypergraph, to implement a learning mechanism, and to construct certain networks.


General Centrality in a hypergraph
Evo Busseniers

http://arxiv.org/abs/1403.5162

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Optimal network clustering for information diffusion

We investigate the impact of community structure on information spreading with the linear threshold model. Contrary to the common belief that communities hinder information diffusion, we show that strong communities can facilitate global cascades by enhancing local, intra-community spreading. Using both analytical approaches and numerical simulations, we demonstrate the existence of optimal clustering, where global cascades require the minimal number of early adopters.

 

Azadeh Nematzadeh, Emilio Ferrara, Alessandro Flammini, Yong-Yeol Ahn

"Optimal network clustering for information diffusion"

arXiv:1401.1257

http://arxiv.org/abs/1401.1257

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june holley's curator insight, May 3, 2014 7:40 AM

Basically states that what we call a Smart Network (loosely connected clusters) is optimal for incubating new ideas and then spreading them.

Stephen Dale's curator insight, May 6, 2014 6:59 AM

Research paper on optimal network structures for information diffusion.

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Collective behavior and the identification of phases in bicycle pelotons

Collective behavior and the identification of phases in bicycle pelotons | Papers | Scoop.it
  • A method for identifying phases in bicycle pelotons is proposed.
  • Collective behavior in bicycle pelotons is characterized by two distinct phases.
  • Lateral synchronization occurs only in the high density phase.
  • High velocities give rise to the low density “stretched” phase.
  • Collective behavior reflects both energy savings and tactics in competition.


Collective behavior and the identification of phases in bicycle pelotons
Hugh Trenchard, Ashlin Richardson, Erick Ratamero, Matjaž Perc

Physica A: Statistical Mechanics and its Applications
Volume 405, 1 July 2014, Pages 92–103

http://dx.doi.org/10.1016/j.physa.2014.03.002

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Creativity, like evolution, is merely a series of thefts

Creativity, like evolution, is merely a series of thefts | Papers | Scoop.it
We can blame evolution for making us little more than the glorified karaoke singers we are. Or as Voltaire put it: "originality is nothing but judicious imitation"

Via Claudia Mihai
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Eli Levine's curator insight, March 15, 2014 1:02 PM

It's all one built upon the other.


What I've been proposing for government is not going to alter the base goals of the political leaders.  In fact, I think it's going to improve their chances of being elected until death, if they follow it correctly, and ultimately preserve our social institutions until the eventual end of the species and, if our descendents are still around, beyond that.

 

What I'm observing, as a political and social scientist, is that through benevolently motivated, effectively sensed and executed policy for the sake of the other in the society, that governments tend to be able to last longer, be more legitimate in the eyes of the public and, ultimately, get carried on, with its members, throughout the generations.

 

Some people simply do not and will not have what it takes to act as these effective, benevolent and empirically grounded leaders, regardless of party affiliation and label.  That is how, I think, our current institutions are failing, because we've populated these political systems with people who don't care, won't care and/or don't have the sense to act for the effective sake of the other for their own sakes.  It's in our legislative systems as well as our administrative systems.  It's killing themselves as much as it's killing our people.  And it's just a brain type who doesn't get the concept of working with others, rather than over or against them.

 

Think about it.

Arjen ten Have's curator insight, March 18, 2014 9:08 AM

Basic but nice essay on how objects of use, creativity and biological evolution are all hung up on the same principles: Hey this works better, what if I combine it with that?

Costas Bouyioukos's curator insight, March 18, 2014 1:40 PM

Mark Pagel writes about our "ability" to innovate.

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Simplicity amid Complexity

We live in interesting times as we watch diverse effects of human activities on Earth's climate emerge from natural variability. In predicting the outcome of this evolving inadvertent experiment, climate science faces many challenges, some of which have been outlined in this series of Science Perspectives (1–6): reducing the uncertainty in climate sensitivity; explaining the recent slowdown in the rate of warming and its implications for understanding internal variability; uncovering the factors that control how and where the land will become drier as it warms; quantifying the cooling due to anthropogenic aerosols; explaining the curious evolution of atmospheric methane; and predicting changes in extreme weather. In addition to these challenges, the turbulent and chaotic atmospheric and oceanic flows seemingly limit predictability on various time scales. Is the climate system just too complex for useful prediction?


Simplicity amid Complexity
Isaac Held

Science 14 March 2014:
Vol. 343 no. 6176 pp. 1206-1207
http://dx.doi.org/10.1126/science.1248447

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Info-computational Constructivism and Cognition

Context: At present, we lack a common understanding of both the process of cognition in living organisms and the construction of knowledge in embodied, embedded cognizing agents in general, including future artifactual cognitive agents under development, such as cognitive robots and softbots. Purpose: This paper aims to show how the info-computational approach (IC) can reinforce constructivist ideas about the nature of cognition and knowledge and, conversely, how constructivist insights (such as that the process of cognition is the process of life) can inspire new models of computing. Method: The info-computational constructive framework is presented for the modeling of cognitive processes in cognizing agents. Parallels are drawn with other constructivist approaches to cognition and knowledge generation. We describe how cognition as a process of life itself functions based on info-computation and how the process of knowledge generation proceeds through interactions with the environment and among agents. Results: Cognition and knowledge generation in a cognizing agent is understood as interaction with the world (potential information), which by processes of natural computation becomes actual information. That actual information after integration becomes knowledge for the agent. Heinz von Foerster is identified as a precursor of natural computing, in particular bio computing. Implications: IC provides a framework for unified study of cognition in living organisms (from the simplest ones, such as bacteria, to the most complex ones) as well as in artifactual cognitive systems. Constructivist content: It supports the constructivist view that knowledge is actively constructed by cognizing agents and shared in a process of social cognition. IC argues that this process can be modeled as info-computation.


Info-computational Constructivism and Cognition
Gordana Dodig-Crnkovic

Constructivist Foundations Volume 9 · Number 2 · Pages 223–231

http://www.univie.ac.at/constructivism/journal/9/2/223.dodig

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Rethinking predators: Legend of the wolf

Rethinking predators: Legend of the wolf | Papers | Scoop.it

On television and in scientific journals, the story of how carnivores influence ecosystems has seized imaginations. From wolves in North America to lions in Africa and dingoes in Australia, top predators are thought to exert tight control over the populations and behaviours of other animals, shaping the entire food web down to the vegetation through a ‘trophic cascade’. This story is popular in part because it supports calls to conserve large carnivores as ‘keystone species’ for whole ecosystems. It also offers the promise of a robust rule within ecology, a field in which researchers have yearned for more predictive power.

But several studies in recent years have raised questions about the top-predator rule in the high-profile cases of the wolf and the dingo. That has led some scientists to suggest that the field’s fascination with top predators stems not from their relative importance, but rather from society’s interest in the big, the dangerous and the vulnerable. “Predators can be important,” says Oswald Schmitz, an ecologist at Yale University in New Haven, Connecticut, “but they aren’t a panacea.”


http://www.nature.com/news/rethinking-predators-legend-of-the-wolf-1.14841

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Sums of variables at the onset of chaos

We explain how specific dynamical properties give rise to the limit distribution of sums of deterministic variables at the transition to chaos via the period-doubling route. We study the sums of successive positions generated by an ensemble of initial conditions uniformly distributed in the entire phase space of a unimodal map as represented by the logistic map. We find that these sums acquire their salient, multiscale, features from the repellor preimage structure that dominates the dynamics toward the attractors along the period-doubling cascade. And we explain how these properties transmit from the sums to their distribution. Specifically, we show how the stationary distribution of sums of positions at the Feigebaum point is built up from those associated with the supercycle attractors forming a hierarchical structure with multifractal and discrete scale invariance properties.

 

Miguel Angel Fuentes, Alberto Robledo
"Sums of variables at the onset of chaos"
The European Physical Journal B, 87:32 (2014)    
http://dx.doi.org/10.1140/epjb/e2014-40882-1

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Geo-located Twitter as proxy for global mobility patterns

Pervasive presence of location-sharing services made it possible for researchers to gain an unprecedented access to the direct records of human activity in space and time. This article analyses geo-located Twitter messages in order to uncover global patterns of human mobility. Based on a dataset of almost a billion tweets recorded in 2012, we estimate the volume of international travelers by country of residence. Mobility profiles of different nations were examined based on such characteristics as mobility rate, radius of gyration, diversity of destinations, and inflow–outflow balance. Temporal patterns disclose the universally valid seasons of increased international mobility and the particular character of international travels of different nations. Our analysis of the community structure of the Twitter mobility network reveals spatially cohesive regions that follow the regional division of the world. We validate our result using global tourism statistics and mobility models provided by other authors and argue that Twitter is exceptionally useful for understanding and quantifying global mobility patterns.


Geo-located Twitter as proxy for global mobility patterns

Bartosz Hawelka*, Izabela Sitko, Euro Beinat, Stanislav Sobolevsky, Pavlos Kazakopoulos & Carlo Ratti

Cartography and Geographic Information Science

http://dx.doi.org/10.1080/15230406.2014.890072
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Shock waves on complex networks

Shock waves on complex networks | Papers | Scoop.it

Power grids, road maps, and river streams are examples of infrastructural networks which are highly vulnerable to external perturbations. An abrupt local change of load (voltage, traffic density, or water level) might propagate in a cascading way and affect a significant fraction of the network. Almost discontinuous perturbations can be modeled by shock waves which can eventually interfere constructively and endanger the normal functionality of the infrastructure. We study their dynamics by solving the Burgers equation under random perturbations on several real and artificial directed graphs. Even for graphs with a narrow distribution of node properties (e.g., degree or betweenness), a steady state is reached exhibiting a heterogeneous load distribution, having a difference of one order of magnitude between the highest and average loads. Unexpectedly we find for the European power grid and for finite Watts-Strogatz networks a broad pronounced bimodal distribution for the loads. To identify the most vulnerable nodes, we introduce the concept of node-basin size, a purely topological property which we show to be strongly correlated to the average load of a node.


Via Claudia Mihai
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Eli Levine's curator insight, March 10, 2014 6:46 PM

Very intuitive and vital to our strategy of defense and preparedness.

 

Start with the homeland.

 

THEN cover the world.

 

If you can do that, honestly.  You'll need popular support of people in order to carry out that kind of feat.

 

Not guns or bombs.

 

Silly generals.

 

Think about it.

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Netconomics: Novel Forecasting Techniques from the Combination of Big Data, Network Science and Economics

The combination of the network theoretic approach with recently available abundant economic data leads to the development of novel analytic and computational tools for modelling and forecasting key economic indicators. The main idea is to introduce a topological component into the analysis, taking into account consistently all higher-order interactions. We present three basic methodologies to demonstrate different approaches to harness the resulting network gain. First, a multiple linear regression optimisation algorithm is used to generate a relational network between individual components of national balance of payment accounts. This model describes annual statistics with a high accuracy and delivers good forecasts for the majority of indicators. Second, an early-warning mechanism for global financial crises is presented, which combines network measures with standard economic indicators. From the analysis of the cross-border portfolio investment network of long-term debt securities, the proliferation of a wide range of over-the-counter-traded financial derivative products, such as credit default swaps, can be described in terms of gross-market values and notional outstanding amounts, which are associated with increased levels of market interdependence and systemic risk. Third, considering the flow-network of goods traded between G-20 economies, network statistics provide better proxies for key economic measures than conventional indicators. For example, it is shown that a country's gate-keeping potential, as a measure for local power, projects its annual change of GDP generally far better than the volume of its imports or exports.


Netconomics: Novel Forecasting Techniques from the Combination of Big Data, Network Science and Economics
Andreas Joseph, Irena Vodenska, Eugene Stanley, Guanrong Chen

http://arxiv.org/abs/1403.0848

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Eli Levine's curator insight, March 12, 2014 10:25 AM

In other words, the more interconnected, bound of and valuable a bank is, the more likely that its failure will result in a global financial crisis.  These banks probably should be broken up, such that there are more nodes and less valuable interconnectivity amongst the banks.

 

The second part, in plain English, basically stated that a country's relative interconnectivity as a node in international trade and the strength of that interconnected trade are greater predictions of economic success than of simple net import/export data.

 

It seems to me that many political leaders and policy makers are not up to date with these latest insights.  This is probably how it is that we're getting the same unevolved, unadapted and negatively effective policies that are driving this country, and the world, into the ground.  On top of that, it's still not addressing our chief problem of being addicted to something that we don't really use and shouldn't really want in excess quantities (money), especially when it's purchased with the opportunity to be well, healthy and survivable as an individual and collective species.

 

It's sad that such a species with such potential should go to waste at this moment over a little ignorance and a very powerful attachment to something that has no bearing on our well being and actual quality of life.

 

Think about it.

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CTL update of Kripke models through protections

We present a nondeterministic, recursive algorithm for updating a Kripke model so as to satisfy a given formula of computation-tree logic (CTL). Recursive algorithms for model update face two dual difficulties: (1) Removing transitions from a Kripke model to satisfy a universal subformula may dissatisfy some existential subformulas. Conversely, (2) adding transitions to satisfy an existential subformula may dissatisfy some universal subformulas. To overcome these difficulties, we employ protections of the form 〈E,A,L〉, recording information about the satisfaction of subformulas previously treated by the algorithm. Intuitively, (1) E is the set of transitions that we cannot remove without compromising the satisfaction of previously treated subformulas. Conversely, (2) A is the set of transitions that we can add. Hence, update proceeds without diminishing E and without augmenting A. Finally, (3) L is a set of literals protecting the model labels. We illustrate our algorithm through several examples: Emerson and Clarke's mutual-exclusion problem, Clarke's microwave-oven example, synchronous counters, and randomly generated models and formulas. In addition, we compare our method with other update approaches for either CTL or fragments of CTL. Lastly, we provide proofs of soundness and completeness and a complexity analysis.


CTL update of Kripke models through protections ☆
Miguel Carrillo, David A. Rosenblueth

Artificial Intelligence, In Press

http://dx.doi.org/10.1016/j.artint.2014.02.005 

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A Genomic Road Map for Complex Human Disease

Despite the successes of genome-wide association studies (GWAS) in identifying genetic connections with human disease, it has become clear that interpreting these data requires a clear understanding of how these new risk genes are regulated. On pages 1118 and 1119 of this issue, Fairfax et al. (1) and Lee et al. (2), respectively, elucidate networks of genetic regulation in the context of the human innate immune system and show how this information can be directly applied to understanding the genetics of autoimmune disorders.


A Genomic Road Map for Complex Human Disease
Peter K. Gregersen

Science 7 March 2014:
Vol. 343 no. 6175 pp. 1087-1088
http://dx.doi.org/10.1126/science.1251426

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From Drivers to Athletes -- Modeling and Simulating Cross-Country Sking Marathons

Traffic flow of athletes in classic-style cross-country ski marathons, with the Swedish Vasaloppet as prominent example, represents a non-vehicular system of driven particles with many properties of vehicular traffic flow such as unidirectional movement, the existence of lanes, and, moreover, severe traffic jams. We propose a microscopic acceleration and track-changing model taking into account different fitness levels, gradients, and interactions between the athletes in all traffic situations. The model is calibrated on microscopic data of the Vasaloppet 2012. Using the multi-model open-source simulator MovSim.org, we simulate all 15 000 participants of the Vasaloppet during the first ten kilometers.


From Drivers to Athletes -- Modeling and Simulating Cross-Country Sking Marathons
Martin Treiber, Ralph Germ, Arne Kesting

http://arxiv.org/abs/1403.4965


See Also:

Crowd Flow Modeling of Athletes in Mass Sports Events -- a Macroscopic Approach
Martin Treiber

http://arxiv.org/abs/1403.4969 

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Local active information storage as a tool to understand distributed neural information processing

Every act of information processing can in principle be decomposed into the component operations of information storage, transfer, and modification. Yet, while this is easily done for today’s digital computers, the application of these concepts to neural information processing was hampered by the lack of proper mathematical definitions of these operations on information. Recently, such definitions were given and the specific concept of local active information storage was successfully applied to the analysis and optimization of artificial neural systems. However, no attempt to measure local active information storage in neural data has been made to date. Here we measure local active information storage on a local scale in time and space in voltage sensitive dye imaging data from area 18 of the cat. We show that storage reflects neural properties such as stimulus preferences and surprise upon unexpected stimulus change, and in area 18 reflects the abstract concept of an ongoing stimulus despite the locally random nature of this stimulus. We suggest that LAIS will be a useful quantity to test theories of cortical function, such as predictive coding.

 

Michael Wibral, Joseph T. Lizier, Sebastian Vögler, Viola Priesemann and Ralf Galuske,

Local active information storage as a tool to understand distributed neural information processing

Frontiers in Neuroinformatics 8:1 (2014)

http://dx.doi.org/10.3389/fninf.2014.00001 

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Data Mining Reveals How Conspiracy Theories Emerge on Facebook

Data Mining Reveals How Conspiracy Theories Emerge on Facebook | Papers | Scoop.it
Some people are more susceptible to conspiracy theories than others, say computational social scientists who have studied how false ideas jump the “credulity barrier” on Facebook.

Conspiracy theories seem to come about by a process in which ordinary satirical commentary or obviously false content somehow jumps the credulity barrier. And that seems to happen through groups of people who deliberately expose themselves to alternative sources of news.


Via Claudia Mihai
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Eli Levine's curator insight, March 18, 2014 4:35 PM

Some people live closer to reality than others.

 

Not surprising.

 

But interesting from a social psychological point of view, which then feeds into a political view, which then leads to credulity and viability for an individual or an individual's beliefs.

 

Think about it.

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Do-It-Yourself Urban Design: The Social Practice of Informal “Improvement” Through Unauthorized Alteration

There are numerous ways in which people make illegal or unauthorized alterations to urban space. This study identifies and analyzes one that has been largely ignored in social science: explicitly functional and civic-minded informal contributions that I call “do-it-yourself urban design.” The research, which began as an investigation into more “traditional” nonpermissable alterations, uncovered these cases—from homemade bike lanes and street signs to guerrilla gardens and development proposals—that are gaining visibility in many cities, yet are poorly accounted for by existing perspectives in the literature. This article examines the existing theories and evidence from interviews and other fieldwork in 14 cities in order to develop the new analytical category of DIY urban design. I present findings on the creators of these interventions, on their motivations to “improve” the built environment where they perceive government and other development actors to be failing, and on the concentration of their efforts in gentrifying areas. This introduces the possibility of conflict and complicates their impact. I argue that DIY urban design has wide-ranging implications for both local communities and broader urban policy.


Do-It-Yourself Urban Design: The Social Practice of Informal “Improvement” Through Unauthorized Alteration
. Gordon C. C. Douglas

City & Community

http://dx.doi.org/10.1111/cico.12029


Via Manu Fernandez
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Molly Martin's curator insight, March 17, 2014 4:55 AM

An interesting read for anyone curious as to how individuals and indie community  organizers rework local infrastructures.

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The Parable of Google Flu: Traps in Big Data Analysis

In February 2013, Google Flu Trends (GFT) made headlines but not for a reason that Google executives or the creators of the flu tracking system would have hoped. Nature reported that GFT was predicting more than double the proportion of doctor visits for influenza-like illness (ILI) than the Centers for Disease Control and Prevention (CDC), which bases its estimates on surveillance reports from laboratories across the United States (1, 2). This happened despite the fact that GFT was built to predict CDC reports. Given that GFT is often held up as an exemplary use of big data (3, 4), what lessons can we draw from this error?


The Parable of Google Flu: Traps in Big Data Analysis
David Lazer, Ryan Kennedy, Gary King, Alessandro Vespignani

Science 14 March 2014:
Vol. 343 no. 6176 pp. 1203-1205
http://dx.doi.org/10.1126/science.1248506

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Turning point: Johan Bollen

Turning point: Johan Bollen | Papers | Scoop.it

Johan Bollen caused a stir in January when he and his colleagues proposed an alternative science-funding model (J. Bollen et al. EMBO Rep. http://doi.org/f2pz34; 2014). Bollen, an informatician at Indiana University Bloomington, explains how the proposal developed, and how the idea of resource allocation became part of his research agenda.

http://www.nature.com/naturejobs/science/articles/10.1038/nj7491-265a

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Storm brewing over WHO sugar proposal

Storm brewing over WHO sugar proposal | Papers | Scoop.it

Scientists are gearing up for a battle with the food industry after the World Health Organization (WHO) moved to halve its recommendation on sugar intake.

Nutrition researchers fear a backlash similar to that seen in 2003, when the WHO released its current guidelines stating that no more than 10% of an adult’s daily calories should come from ‘free’ sugars. That covers those added to food, as well as natural sugars in honey, syrups and fruit juice. In 2003, the US Sugar Association, a powerful food-industry lobby group based in Washington DC, pressed the US government to withdraw funding for the WHO if the organization did not modify its recommendations. The WHO did not back down, and has now mooted cutting the level to 5%.

http://www.nature.com/news/storm-brewing-over-who-sugar-proposal-1.14854

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The Bursty Dynamics of the Twitter Information Network

In online social media systems users are not only posting, consuming, and resharing content, but also creating new and destroying existing connections in the underlying social network. While each of these two types of dynamics has individually been studied in the past, much less is known about the connection between the two. How does user information posting and seeking behavior interact with the evolution of the underlying social network structure?
Here, we study ways in which network structure reacts to users posting and sharing content. We examine the complete dynamics of the Twitter information network, where users post and reshare information while they also create and destroy connections. We find that the dynamics of network structure can be characterized by steady rates of change, interrupted by sudden bursts. Information diffusion in the form of cascades of post re-sharing often creates such sudden bursts of new connections, which significantly change users' local network structure. These bursts transform users' networks of followers to become structurally more cohesive as well as more homogenous in terms of follower interests. We also explore the effect of the information content on the dynamics of the network and find evidence that the appearance of new topics and real-world events can lead to significant changes in edge creations and deletions. Lastly, we develop a model that quantifies the dynamics of the network and the occurrence of these bursts as a function of the information spreading through the network. The model can successfully predict which information diffusion events will lead to bursts in network dynamics.


The Bursty Dynamics of the Twitter Information Network
Seth A. Myers, Jure Leskovec

http://arxiv.org/abs/1403.2732

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Scientometrics: Untangling the topics

Measuring science is based on comparing articles to similar others. However, keyword-based groups of thematically similar articles are dominantly small. This keeps statistical errors high. With the growing availability of bibliographic data these statistical errors can be reduced by merging methods of thematic grouping, citation networks and keyword co-usage networks.


Scientometrics: Untangling the topics
Adam Szanto-Varnagy, Peter Pollner, Tamas Vicsek, Illes J. Farkas

http://arxiv.org/abs/1403.2140

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Model versions and fast algorithms for network epidemiology

Network epidemiology has become a core framework for investigating the role of human contact patterns in the spreading of infectious diseases. In network epidemiology represents the contact structure as a network of nodes (individuals) connected by links (sometimes as a temporal network where the links are not continuously active) and the disease as a compartmental model (where individuals are assigned states with respect to the disease and follow certain transition rules between the states). In this paper, we discuss fast algorithms for such simulations and also compare two commonly used versions - one where there is a constant recovery rate (the number of individuals that stop being infectious per time is proportional to the number of such people), the other where the duration of the disease is constant. We find that, for most practical purposes, these versions are qualitatively the same.


Model versions and fast algorithms for network epidemiology
Petter Holme

http://arxiv.org/abs/1403.1011

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Predicting Scientific Success Based on Coauthorship Networks

We address the question to what extent the success of scientific articles is due to social influence. Analyzing a data set of over 100000 publications from the field of Computer Science, we study how centrality in the coauthorship network differs between authors who have highly cited papers and those who do not. We further show that a machine learning classifier, based only on coauthorship network centrality measures at time of publication, is able to predict with high precision whether an article will be highly cited five years after publication. By this we provide quantitative insight into the social dimension of scientific publishing - challenging the perception of citations as an objective, socially unbiased measure of scientific success.


Predicting Scientific Success Based on Coauthorship Networks
Emre Sarigöl, Rene Pfitzner, Ingo Scholtes, Antonios Garas, Frank Schweitzer

http://arxiv.org/abs/1402.7268

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Correlation of automorphism group size and topological properties with program-size complexity evaluations of graphs and complex networks

We show that numerical approximations of Kolmogorov complexity (K) of graphs and networks capture some group-theoretic and topological
properties of empirical networks, ranging from metabolic to social
networks, and of small synthetic networks that we have produced. That
K and the size of the group of automorphisms of a graph are correlated
opens up interesting connections to problems in computational
geometry, and thus connects several measures and concepts from
complexity science. We derive these results via two different
Kolmogorov complexity approximation methods applied to the adjacency
matrices of the graphs and networks. The methods used are the
traditional lossless compression approach to Kolmogorov complexity,
and a normalized version of a Block Decomposition Method (BDM) based
on algorithmic probability theory.


Correlation of automorphism group size and topological properties with
program-size complexity evaluations of graphs and complex networks
H. Zenil et al.
Physica A: Statistical Mechanics and its Applications, 2014
http://www.sciencedirect.com/science/article/pii/S0378437114001691

Preprint available: http://arxiv.org/abs/1306.0322

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