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SOCNET  April 2014

SOCNET April 2014

Subject:

Selected Latest Complexity Digest Posts (fwd)

From:

Barry Wellman <[log in to unmask]>

Reply-To:

Barry Wellman <[log in to unmask]>

Date:

Tue, 15 Apr 2014 09:39:55 -0400

Content-Type:

MULTIPART/MIXED

Parts/Attachments:

Parts/Attachments

TEXT/PLAIN (163 lines)

*****  To join INSNA, visit http://www.insna.org  *****


   Barry Wellman
  _______________________________________________________________________

   NetLab                        FRSC                      INSNA Founder
   Faculty of Information (iSchool)                 611 Bissell Building
   140 St. George St.    University of Toronto    Toronto Canada M5S 3G6
   http://www.chass.utoronto.ca/~wellman          twitter: @barrywellman
                  NSA/CSEC: Canadian and American citizen
   NETWORKED:The New Social Operating System. Lee Rainie & Barry Wellman
   MIT Press            http://amzn.to/zXZg39      Print $14  Kindle $16
                  Old/NewCyberTimes http://bit.ly/c8N9V8
   ________________________________________________________________________


---------- Forwarded message ----------
Date: Mon, 14 Apr 2014 21:15:51 -0500
From: Complexity Digest Administration <[log in to unmask]>
To: [log in to unmask]
Subject: [comdig] Latest Complexity Digest Posts


Crisis Responses and Crisis Management: what can we learn from Biological Networks?

    The generality of network properties allows the utilization of the ˙˙wisdom˙˙ of biological systems surviving crisis events for many millions of years. Yeast protein-protein interaction network shows a decrease in community-overlap (an increase in community cohesion) in stress. Community rearrangement seems to be a cost-efficient, general crisis-management response of complex systems. Inter-community bridges, such as the highly dynamic ˙˙creative nodes˙˙ emerge as crucial determinants helping crisis survival.

Crisis Responses and Crisis Management: what can we learn from Biological Networks?
Péter Csermely, Agoston Mihalik, Zsolt Vassy, András London

Systema: connecting matter, life, culture and technology

Vol 2, No 1 (2014)

http://www.systema-journal.org/article/view/115

See it on Scoop.it (http://www.scoop.it/t/papers/p/4019372992/2014/04/12/crisis-responses-and-crisis-management-what-can-we-learn-from-biological-networks) , via Papers (http://www.scoop.it/t/papers)


Hierarchical Block Structures and High-Resolution Model Selection in Large Networks

    Social, technological, and biological networks are known to organize into modules or ˙˙communities.˙˙ Characterizing and identifying modules is highly nontrivial and still an outstanding problem in networks research. A new approach uses both the concept of modular hierarchy for network construction and the methods of statistical inference to address this problem, succeeding where the existing approaches see difficulties.

Hierarchical Block Structures and High-Resolution Model Selection in Large Networks
Tiago P. Peixoto
Phys. Rev. X 4, 011047 (2014)

http://dx.doi.org/10.1103/PhysRevX.4.011047

See it on Scoop.it (http://www.scoop.it/t/papers/p/4019448103/2014/04/12/hierarchical-block-structures-and-high-resolution-model-selection-in-large-networks) , via Papers (http://www.scoop.it/t/papers)


Information Flow in Animal-Robot Interactions

    The nonverbal transmission of information between social animals is a primary driving force behind their actions and, therefore, an important quantity to measure in animal behavior studies. Despite its key role in social behavior, the flow of information has only been inferred by correlating the actions of individuals with a simplifying assumption of linearity. In this paper, we leverage information-theoretic tools to relax this assumption. To demonstrate the feasibility of our approach, we focus on a robotics-based experimental paradigm, which affords consistent and controllable delivery of visual stimuli to zebrafish. Specifically, we use a robotic arm to maneuver a life-sized replica of a zebrafish in a predetermined trajectory as it interacts with a focal subject in a test tank. We track the fish and the replica through time and use the resulting trajectory data to measure the transfer entropy between the replica and the focal subject, which, in turn, is used to quantify
one-directional information flow from the robot to the fish. In agreement with our expectations, we find that the information flow from the replica to the zebrafish is significantly more than the other way around. Notably, such information is specifically related to the response of the fish to the replica, whereby we observe that the information flow is reduced significantly if the motion of the replica is randomly delayed in a surrogate dataset. In addition, comparison with a control experiment, where the replica is replaced by a conspecific, shows that the information flow toward the focal fish is significantly more for a robotic than a live stimulus. These findings support the reliability of using transfer entropy as a measure of information flow, while providing indirect evidence for the efficacy of a robotics-based platform in animal behavioral studies.

Information Flow in Animal-Robot Interactions
by Sachit Butail, Fabrizio Ladu, Davide Spinello and Maurizio Porfiri
Entropy 2014, 16(3), 1315-1330; doi:10.3390/e16031315
http://www.mdpi.com/1099-4300/16/3/1315/

See it on Scoop.it (http://www.scoop.it/t/papers/p/4019446725/2014/04/11/information-flow-in-animal-robot-interactions) , via Papers (http://www.scoop.it/t/papers)


Evolutionary Multiplayer Games

    Evolutionary game theory has become one of the most diverse and far reaching theories in biology. Applications of this theory range from cell dynamics to social evolution. However, many applications make it clear that inherent non-linearities of natural systems need to be taken into account. One way of introducing such non-linearities into evolutionary games is by the inclusion of multiple players. An example is of social dilemmas, where group benefits could e.g.\ increase less than linear with the number of cooperators. Such multiplayer games can be introduced in all the fields where evolutionary game theory is already well established. However, the inclusion of non-linearities can help to advance the analysis of systems which are known to be complex, e.g. in the case of non-Mendelian inheritance. We review the diachronic theory and applications of multiplayer evolutionary games and present the current state of the field. Our aim is a summary of the theoretical results from
well-mixed populations in infinite as well as finite populations. We also discuss examples from three fields where the theory has been successfully applied, ecology, social sciences and population genetics. In closing, we probe certain future directions which can be explored using the complexity of multiplayer games while preserving the promise of simplicity of evolutionary games.

Evolutionary Multiplayer Games
Chaitanya S. Gokhale, Arne Traulsen

http://arxiv.org/abs/1404.1421

See it on Scoop.it (http://www.scoop.it/t/papers/p/4019379880/2014/04/10/evolutionary-multiplayer-games) , via Papers (http://www.scoop.it/t/papers)



Revealing the structure of the world airline network

    Resilience of most critical infrastructures against failure of elements that appear insignificant is usually taken for granted. The World Airline Network (WAN) is an infrastructure that reduces the geographical gap between societies, both small and large, and brings forth economic gains. With the extensive use of a publicly maintained data set that contains information about airports and alternative connections between these airports, we empirically reveal that the WAN is a redundant and resilient network for long distance air travel, but otherwise breaks down completely due to removal of short and apparently insignificant connections. These short range connections with moderate number of passengers and alternate flights are the connections that keep remote parts of the world accessible. It is surprising, insofar as there exists a highly resilient and strongly connected core consisting of a small fraction of airports (around 2.3%) together with an extremely fragile star-like
periphery. Yet, in spite of their relevance, more than 90% of the world airports are still interconnected upon removal of this core. With standard and unconventional removal measures we compare both empirical and topological perceptions for the fragmentation of the world. We identify how the WAN is organized into different classes of clusters based on the physical proximity of airports and analyze the consequence of this fragmentation.

Revealing the structure of the world airline network
Trivik Verma, Nuno A. M. Araújo, Hans J Herrmann

http://arxiv.org/abs/1404.1368

See it on Scoop.it (http://www.scoop.it/t/papers/p/4019388089/2014/04/10/revealing-the-structure-of-the-world-airline-network) , via Papers (http://www.scoop.it/t/papers)



Spreading dynamics on networks: the role of burstiness, topology and stationarity

    Spreading on networks is influenced by a number of factors including different parts of the inter-event time distribution (IETD), the topology of the network and nonstationarity. In order to understand the role of these factors we study the SI model on temporal networks with different aggregated topologies and different IETDs. Based on analytic calculations and numerical simulations, we show that if the stationary bursty process is governed by power-law IETD, the spreading can be slowed down or accelerated as compared to a Poisson process; the speed is determined by the short time behaviour, which in our model is controlled by the exponent. We demonstrate that finite, so called "locally tree-like" networks, like the Barab\'asi-Albert networks behave very differently from real tree graphs if the IETD is strongly fat-tailed, as the lack or presence of rare alternative paths modifies the spreading. A further important result is that the non-stationarity of the dynamics has a
significant effect on the spreading speed for strongly fat-tailed power-law IETDs, thus bursty processes characterized by small power-law exponents can cause slow spreading in the stationary state but also very rapid spreading heavily depending on the age of the processes.

Spreading dynamics on networks: the role of burstiness, topology and stationarity
Dávid X. Horváth, János Kertész

http://arxiv.org/abs/1404.2468

See it on Scoop.it (http://www.scoop.it/t/papers/p/4019377840/2014/04/10/spreading-dynamics-on-networks-the-role-of-burstiness-topology-and-stationarity) , via Papers (http://www.scoop.it/t/papers)




Network Weirdness: Exploring the Origins of Network Paradoxes

    Social networks have many counter-intuitive properties, including the "friendship paradox" that states, on average, your friends have more friends than you do. Recently, a variety of other paradoxes were demonstrated in online social networks. This paper explores the origins of these network paradoxes. Specifically, we ask whether they arise from mathematical properties of the networks or whether they have a behavioral origin. We show that sampling from heavy-tailed distributions always gives rise to a paradox in the mean, but not the median. We propose a strong form of network paradoxes, based on utilizing the median, and validate it empirically using data from two online social networks. Specifically, we show that for any user the majority of user's friends and followers have more friends, followers, etc. than the user, and that this cannot be explained by statistical properties of sampling. Next, we explore the behavioral origins of the paradoxes by using the shuffle test
to remove correlations between node degrees and attributes. We find that paradoxes for the mean persist in the shuffled network, but not for the median. We demonstrate that strong paradoxes arise due to the assortativity of user attributes, including degree, and correlation between degree and attribute.

Network Weirdness: Exploring the Origins of Network Paradoxes
Farshad Kooti, Nathan O. Hodas, Kristina Lerman

http://arxiv.org/abs/1403.7242

See it on Scoop.it (http://www.scoop.it/t/papers/p/4018995835/2014/04/09/network-weirdness-exploring-the-origins-of-network-paradoxes) , via Papers (http://www.scoop.it/t/papers)



Eight (No, Nine!) Problems With Big Data

    BIG data is suddenly everywhere. Everyone seems to be collecting it, analyzing it, making money from it and celebrating (or fearing) its powers. Whether we˙˙re talking about analyzing zillions of Google search queries to predict flu outbreaks, or zillions of phone records to detect signs of terrorist activity, or zillions of airline stats to find the best time to buy plane tickets, big data is on the case. By combining the power of modern computing with the plentiful data of the digital era, it promises to solve virtually any problem ˙˙ crime, public health, the evolution of grammar, the perils of dating ˙˙ just by crunching the numbers.

See it on Scoop.it (http://www.scoop.it/t/papers/p/4019230296/2014/04/08/eight-no-nine-problems-with-big-data) , via Papers (http://www.scoop.it/t/papers)



Behavioral and Network Origins of Wealth Inequality: Insights from a Virtual World

    Almost universally, wealth is not distributed uniformly within societies or economies. Even though wealth data have been collected in various forms for centuries, the origins for the observed wealth-disparity and social inequality are not yet fully understood. Especially the impact and connections of human behavior on wealth could so far not be inferred from data. Here we study wealth data from the virtual economy of the massive multiplayer online game (MMOG) Pardus. This data not only contains every player's wealth at every point in time, but also all actions of every player over a timespan of almost a decade. We find that wealth distributions in the virtual world are very similar to those in western countries. In particular we find an approximate exponential for low wealth and a power-law tail. The Gini index is found to be
g=0.65, which is close to the indices of many Western countries. We find that wealth-increase rates depend on the time when players entered the game. Players that entered the game early on tend to have remarkably higher wealth-increase rates than those who joined later. Studying the players' positions within their social networks, we find that the local position in the trade network is most relevant for wealth. Wealthy people have high in- and out-degree in the trade network, relatively low nearest-neighbor degree and a low clustering coefficient. Wealthy players have many mutual friendships and are socially well respected by others, but spend more time on business than on socializing. We find that players that are not organized within social groups with at least three members are significantly poorer on average. We observe that high `political' status and high wealth go hand in hand. Wealthy players have few personal enemies, but show animosity towards players that behave as
public enemies.

Behavioral and Network Origins of Wealth Inequality: Insights from a Virtual World
Benedikt Fuchs, Stefan Thurner

http://arxiv.org/abs/1403.6342

See it on Scoop.it (http://www.scoop.it/t/papers/p/4018995000/2014/04/08/behavioral-and-network-origins-of-wealth-inequality-insights-from-a-virtual-world) , via Papers (http://www.scoop.it/t/papers)


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