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SOCNET  July 2014

SOCNET July 2014

Subject:

Selected Latest Complexity Digest Posts (fwd)

From:

Barry Wellman <[log in to unmask]>

Reply-To:

Barry Wellman <[log in to unmask]>

Date:

Mon, 7 Jul 2014 10:21:17 -0400

Content-Type:

MULTIPART/MIXED

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TEXT/PLAIN (182 lines)

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




   Barry Wellman
  _______________________________________________________________________

                      Faculty of Information (iSchool)
   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, 7 Jul 2014 08:52:01 -0500
From: Complexity Digest Administration <[log in to unmask]>
To: [log in to unmask]
Subject: [comdig] Latest Complexity Digest Posts

Learn about the latest and greatest related to complex systems research. More at http://comdig.unam.mx



The scaling of human interactions with city size

    The size of cities is known to play a fundamental role in social and economic life. Yet, its relation to the structure of the underlying network of human interactions has not been investigated empirically in detail. In this paper, we map society-wide communication networks to the urban areas of two European countries. We show that both the total number of contacts and the total communication activity grow superlinearly with city population size, according to well-defined scaling relations and resulting from a multiplicative increase that affects most citizens. Perhaps surprisingly, however, the probability that an individual's contacts are also connected with each other remains largely unaffected. These empirical results predict a systematic and scale-invariant acceleration of interaction-based spreading phenomena as cities get bigger, which is numerically confirmed by applying epidemiological models to the studied networks. Our findings should provide a microscopic basis
towards understanding the superlinear increase of different socioeconomic quantities with city size, that applies to almost all urban systems and includes, for instance, the creation of new inventions or the prevalence of certain contagious diseases.

Markus Schläpfer, Luís M. A. Bettencourt, Sébastian Grauwin, Mathias Raschke, Rob Claxton, Zbigniew Smoreda, Geoffrey B. West, and Carlo Ratti
The scaling of human interactions with city size
J. R. Soc. Interface. 2014 11 20130789; http://dx.doi.org/10.1098/rsif.2013.0789

See it on Scoop.it (http://www.scoop.it/t/papers/p/4023956536/2014/07/06/the-scaling-of-human-interactions-with-city-size) , via Papers (http://www.scoop.it/t/papers)


The birth of cooperation

    Mutually beneficial associations between individuals of different species, called mutualistic symbioses, have enabled major ecological innovations and underlie some of the major transitions in evolution. For example, the ancestor of plants domesticated endosymbiotic photosynthetic bacteria, today's chloroplasts, for carbon fixation. This association dramatically increased the habitat of these photosynthetic bacteria from the sea to terrestrial ecosystems. However, the colonization of land by plants required an additional symbiotic association, with fungal root symbionts that facilitate nutrient uptake. Yet, surprisingly little is known about how mutualistic symbioses evolved and persist.

The birth of cooperation
Duur K. Aanen, Ton Bisseling

Science 4 July 2014:
Vol. 345 no. 6192 pp. 29-30
http://dx.doi.org/10.1126/science.1256542

See it on Scoop.it (http://www.scoop.it/t/papers/p/4024092420/2014/07/05/the-birth-of-cooperation) , via Papers (http://www.scoop.it/t/papers)



The structure and dynamics of multilayer networks

    In the past years, network theory has successfully characterized the interaction among the constituents of a variety of complex systems, ranging from biological to technological, and social systems. However, up until recently, attention was almost exclusively given to networks in which all components were treated on equivalent footing, while neglecting all the extra information about the temporal- or context-related properties of the interactions under study. Only in the last years, taking advantage of the enhanced resolution in real data sets, network scientists have directed their interest to the multiplex character of real-world systems, and explicitly considered the time-varying and multilayer nature of networks. We offer here a comprehensive review on both structural and dynamical organization of graphs made of diverse relationships (layers) between its constituents, and cover several relevant issues, from a full redefinition of the basic structural measures, to
understanding how the multilayer nature of the network affects processes and dynamics.

The structure and dynamics of multilayer networks
S. Boccaletti, G. Bianconi, R. Criado, C.I. del Genio, J. Gómez-Gardeńes, M. Romance, I. Sendińa-Nadal, Z. Wang, M. Zanin

http://arxiv.org/abs/1407.0742

See it on Scoop.it (http://www.scoop.it/t/papers/p/4024092002/2014/07/04/the-structure-and-dynamics-of-multilayer-networks) , via Papers (http://www.scoop.it/t/papers)


Emergence and persistence of communities in coevolutionary networks

    We investigate the emergence and persistence of communities through a recently proposed mechanism of adaptive rewiring in coevolutionary networks. We characterize the topological structures arising in a coevolutionary network subject to an adaptive rewiring process and a node dynamics given by a simple voterlike rule. We find that, for some values of the parameters describing the adaptive rewiring process, a community structure emerges on a connected network. We show that the emergence of communities is associated to a decrease in the number of active links in the system, i.e. links that connect two nodes in different states. The lifetime of the community structure state scales exponentially with the size of the system. Additionally, we find that a small noise in the node dynamics can sustain a diversity of states and a community structure in time in a finite size system. Thus, large system size and/or local noise can explain the persistence of communities and diversity in
many real systems.

Emergence and persistence of communities in coevolutionary networks
J. C. González-Avella, M. G. Cosenza, J. L. Herrera, K. Tucci

http://arxiv.org/abs/1407.0388

See it on Scoop.it (http://www.scoop.it/t/papers/p/4024091353/2014/07/04/emergence-and-persistence-of-communities-in-coevolutionary-networks) , via Papers (http://www.scoop.it/t/papers)



Against the Smart City

    Post by Michael Batty

Absolutely the best thing to read on the corporate hype and innuendos from
the big computer companies pedalling the idea of ˙˙the smart city˙˙. Adam
Greenfield˙˙s new book ˙˙ that you can only get on Kindle and which was my
first Kindle purchase that I read on my iPad (a success I must say) ˙˙ is
a wonderful and eloquent essay on the extreme hype surrounding the top
down new town-like smart cities of Songdo (in South Korea), Masdar (in the
UAE), PlanIT Valley (near Paredes in Portugal). He also comments on
Singapore, Rio de Janeiro and some of the other established cities who are
injecting automation into their urban services and other functions from
the top down. His message is that most of the smart cities hype associated
with IBM, Cisco, and Siemens amongst others which he recounts in detail is
based on the most simplistic of notions as to what a city actually is.

(...)

See it on Scoop.it (http://www.scoop.it/t/papers/p/4023967477/2014/07/02/against-the-smart-city) , via Papers (http://www.scoop.it/t/papers)



Motif statistics of artificially evolved and biological networks

    Topological features of gene regulatory networks can be successfully reproduced by a model population evolving under selection for short dynamical attractors. The evolved population of networks exhibit motif statistics, summarized by significance profiles, which closely match those of E. coli, S. cerevsiae, and B. subtilis, in such features as the excess of linear motifs and feedforward loops, and deficiency of feedback loops. The slow relaxation to stasis is a hallmark of a rugged fitness landscape, with independently evolving populations exploring distinct valleys strongly differing in network properties.


Burçin Danac˙˙, Mehmet Ali An˙˙l, and Ay˙˙e Erzan
Motif statistics of artificially evolved and biological networks
Phys. Rev. E 89, 062719 (2014)

See it on Scoop.it (http://www.scoop.it/t/papers/p/4023916940/2014/07/02/motif-statistics-of-artificially-evolved-and-biological-networks) , via Papers (http://www.scoop.it/t/papers)



Current innovations and future challenges of network motif detection

    Network motif detection is the search for statistically overrepresented subgraphs present in a larger target network. They are thought to represent key structure and control mechanisms. Although the problem is exponential in nature, several algorithms and tools have been developed for efficiently detecting network motifs. This work analyzes 11 network motif detection tools and algorithms. Detailed comparisons and insightful directions for using these tools and algorithms are discussed. Key aspects of network motif detection are investigated. Network motif types and common network motifs as well as their biological functions are discussed. Applications of network motifs are also presented. Finally, the challenges, future improvements and future research directions for network motif detection are also discussed.


Ngoc Tam L. Tran, Sominder Mohan, Zhuoqing Xu, Chun-Hsi Huang
Current innovations and future challenges of network motif detection
Briefings in Bioinformatics (2014), to appear
http://dx.doi.org/10.1093/bib/bbu021

See it on Scoop.it (http://www.scoop.it/t/papers/p/4023917578/2014/07/02/current-innovations-and-future-challenges-of-network-motif-detection) , via Papers (http://www.scoop.it/t/papers)



ECCS WARM-UP: II School on Complex Networks, Sept 19-21, 2014, Lucca

    Following last years successful edition, we have once more decided to organize a summer school coinciding with the European Conference on Complex Systems thus profiting the opportunity offered by the presence of a wide variety of experts in different topics in Lucca. The projected school aims to offer young researchers the opportunity to learn new methods, present their work and meet fellow researchers, and it also represents a good opportunity for young researcher to prepare their participation to the main ECCS conference in an informal and relaxed environment.
Following our policy to display local talent, three renowned italian researchers will each present a different aspect of complex networks in three hour sessions. Names such as Dr. Roberta Sinatra, Dr. Ciro Catutto and Prof. Stefano Battiston should sound familiar to any interested student. Furthermore, we plan a meeting where each participant will have the possibility to share with the others his work, organized as a flash presentation workshop. Of course, a major social event is also included, to stimulate networking and ˙˙prepare˙˙ the official ECCS conference.

http://eccswarmup.wordpress.com

See it on Scoop.it (http://www.scoop.it/t/cxconferences/p/4023916175/2014/07/02/eccs-warm-up-ii-school-on-complex-networks-sept-19-21-2014-lucca) , via CxConferences (http://www.scoop.it/t/cxconferences)



Thinking Big: How the Evolution of Social Life Shaped the Human Mind (by Robin Dunbar et al.)

    A closer look at genealogy, incorporating how biological, anthropological, and technical factors can influence human lives

We are at a pivotal moment in understanding our remote ancestry and its implications for how we live today. The barriers to what we can know about our distant relatives have been falling as a result of scientific advance, such as decoding the genomes of humans and Neanderthals, and bringing together different perspectives to answer common questions. These collaborations have brought new knowledge and suggested fresh concepts to examine. The results have shaken the old certainties.

The results are profound; not just for the study of the past but for appreciating why we conduct our social lives in ways, and at scales, that are familiar to all of us. But such basic familiarity raises a dilemma. When surrounded by the myriad technical and cultural innovations that support our global, urbanized lifestyles we can lose sight of the small social worlds we actually inhabit and that can be traced deep into our ancestry. So why do we need art, religion, music, kinship, myths, and all the other facets of our over-active imaginations if the reality of our effective social worlds is set by a limit of some one hundred and fifty partners (Dunbar˙˙s number) made of family, friends, and useful acquaintances? How could such a social community lead to a city the size of London or a country as large as China? Do we really carry our hominin past into our human present? It is these small worlds, and the link they allow to the study of the past that forms the central point in
this book.



CASM: Thematic series on Modeling large-scale communication networks using complex networks and agent-based modeling techniques

    Complex Adaptive Systems Modeling welcomes submissions to the new thematic series on Modeling large-scale communication networks using complex networks and agent-based modeling techniques.
This thematic series intends to publish high quality original research as well as review articles on case studies, models and methods for the modeling and simulation of large-scale computer communication networks using either of the following two approaches:
* Complex networks (such as modeled using tools such as Gephi, Network Workbench and others)
* Agent-based models (such as based on NetLogo, Repast, Mason, Swarm and others)

Potential topics include, but are not limited to:
* Multiagent systems
* Cognitive Sensor Networks
* Wireless Sensor Networks
* Sensor Actuator Networks
* Cloud computing infra-structures
* Internet of Things
* Service-oriented architectures
* Pervasive/Mobile Computing
* Peer-to-peer networks

http://www.casmodeling.com/about/update/COMM_NETS

See it on Scoop.it (http://www.scoop.it/t/cxannouncements/p/4023890385/2014/07/01/casm-thematic-series-on-modeling-large-scale-communication-networks-using-complex-networks-and-agent-based-modeling-techniques) , via CxAnnouncements (http://www.scoop.it/t/cxannouncements)

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