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SOCNET  September 2014

SOCNET September 2014

Subject:

selected [comdig] Latest Complexity Digest Posts (fwd)

From:

Barry Wellman <[log in to unmask]>

Reply-To:

Barry Wellman <[log in to unmask]>

Date:

Mon, 1 Sep 2014 15:58:18 -0400

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

   Barry Wellman
  _______________________________________________________________________
   FRSC		              NetLab Network              INSNA Founder
                      Faculty of Information (iSchool)
   University of Toronto                          Toronto Canada M5S 3G6
   http://www.chass.utoronto.ca/~wellman          twitter: @barrywellman
   NETWORKED:The New Social Operating System. Lee Rainie & Barry Wellman
   MIT Press            http://amzn.to/zXZg39      Print $15  Kindle $9
                  Old/NewCyberTimes http://bit.ly/c8N9V8
   ________________________________________________________________________


---------- Forwarded message ----------
Date: Mon, 1 Sep 2014 12:06:16 -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 Matthew effect in empirical data

    The Matthew effect describes the phenomenon that in societies the rich tend to get richer and the potent even more powerful. It is closely related to the concept of preferential attachment in network science, where the more connected nodes are destined to acquire many more links in the future than the auxiliary nodes. Cumulative advantage and success-breads-success also both describe the fact that advantage tends to beget further advantage. The concept is behind the many power laws and scaling behaviour in empirical data, and it is at the heart of self-organization across social and natural sciences. Here we review the methodology for measuring preferential attachment in empirical data, as well as the observations of the Matthew effect in patterns of scientific collaboration, socio-technical and biological networks, the propagation of citations, the emergence of scientific progress and impact, career longevity, the evolution of common English words and phrases, as well a!
 s in
education and brain development. We also discuss whether the Matthew effect is due to chance or optimisation, for example related to homophily in social systems or efficacy in technological systems, and we outline possible directions for future research.

The Matthew effect in empirical data
Matjaz Perc

http://arxiv.org/abs/1408.5124

See it on Scoop.it (http://www.scoop.it/t/papers/p/4027111850/2014/08/30/the-matthew-effect-in-empirical-data) , via Papers (http://www.scoop.it/t/papers)



    If your social media feeds haven?t been clogged with videos of the ALS Ice Bucket Challenge this week, then you?re in the minority.
The campaign involves people dumping buckets of ice water on themselves (or being doused by others), sharing a video of the experience and nominating others to give it a try as a way to build awareness of amyotrophic lateral sclerosis (ALS.) Otherwise known as ?Lou Gehrig?s Disease,? ALS is a progressive disease that causes nerve cells to deteriorate and eventually leads to total paralysis and death.

See it on Scoop.it (http://www.scoop.it/t/papers/p/4027112913/2014/08/29/why-the-als-ice-bucket-challenge-went-viral) , via Papers (http://www.scoop.it/t/papers)



Longitudinal analysis of microbial interaction between humans and the indoor environment

    The bacteria that colonize humans and our built environments have the potential to influence our health. Microbial communities associated with seven families and their homes over 6 weeks were assessed, including three families that moved their home. Microbial communities differed substantially among homes, and the home microbiome was largely sourced from humans. The microbiota in each home were identifiable by family. Network analysis identified humans as the primary bacterial vector, and a Bayesian method significantly matched individuals to their dwellings. Draft genomes of potential human pathogens observed on a kitchen counter could be matched to the hands of occupants. After a house move, the microbial community in the new house rapidly converged on the microbial community of the occupants? former house, suggesting rapid colonization by the family?s microbiota.

Longitudinal analysis of microbial interaction between humans and the indoor environment
. Simon Lax, et al.

Science 29 August 2014:
Vol. 345 no. 6200 pp. 1048-1052
http://dx.doi.org/10.1126/science.1254529

See it on Scoop.it (http://www.scoop.it/t/papers/p/4027106910/2014/08/29/longitudinal-analysis-of-microbial-interaction-between-humans-and-the-indoor-environment) , via Papers (http://www.scoop.it/t/papers)



Controlling extreme events on complex networks

    Extreme events, a type of collective behavior in complex networked dynamical systems, often can have catastrophic consequences. To develop effective strategies to control extreme events is of fundamental importance and practical interest. Utilizing transportation dynamics on complex networks as a prototypical setting, we find that making the network ?mobile? can effectively suppress extreme events. A striking, resonance-like phenomenon is uncovered, where an optimal degree of mobility exists for which the probability of extreme events is minimized. We derive an analytic theory to understand the mechanism of control at a detailed and quantitative level, and validate the theory numerically. Implications of our finding to current areas such as cybersecurity are discussed.

Controlling extreme events on complex networks
? Yu-Zhong Chen, Zi-Gang Huang & Ying-Cheng Lai

Scientific Reports 4, Article number: 6121 http://dx.doi.org/10.1038/srep06121

See it on Scoop.it (http://www.scoop.it/t/papers/p/4027051602/2014/08/28/controlling-extreme-events-on-complex-networks) , via Papers (http://www.scoop.it/t/papers)



Evolving Modular Genetic Regulatory Networks with a Recursive, Top-Down Approach

    Being able to design genetic regulatory networks (GRNs) to achieve a desired cellular function is one of the main goals of synthetic biology. However, determining minimal GRNs that produce desired time-series behaviors is non-trivial. In this paper, we propose a 'top-down' approach to evolving small GRNs and then use these to recursively boot-strap the identification of larger, more complex, modular GRNs. We start with relatively dense GRNs and then use differential evolution (DE) to evolve interaction coefficients. When the target dynamical behavior is found embedded in a dense GRN, we narrow the focus of the search and begin aggressively pruning out excess interactions at the end of each generation. We first show that the method can quickly rediscover known small GRNs for a toggle switch and an oscillatory circuit. Next we include these GRNs as non-evolvable subnetworks in the subsequent evolution of more complex, modular GRNs. Successful solutions found in canonical DE
where we truncated small interactions to zero, with or without an interaction penalty term, invariably contained many excess interactions. In contrast, by incorporating aggressive pruning and the penalty term, the DE was able to find minimal or nearly minimal GRNs in all test problems.


"Evolving Modular Genetic Regulatory Networks with a Recursive, Top-Down Approach"
Javier Garcia-Bernardo, Margaret J. Eppstein
arXiv:1408.5380, 2014
http://arxiv.org/abs/1408.5380

See it on Scoop.it (http://www.scoop.it/t/papers/p/4026836621/2014/08/26/evolving-modular-genetic-regulatory-networks-with-a-recursive-top-down-approach) , via Papers (http://www.scoop.it/t/papers)


The Transferrable Postdoc

    Now more than ever, experts say, postdoctoral fellows need to cultivate a broad base of beyond-the-bench skills and capitalize on transferring them to the next stage of their career to be as competitive as possible. In today?s competitive job market, it is vitally important for postdocs to accumulate skill sets on their CVs right alongside their publications?whether their next career move is research-based or not. Postdocs who repurpose their lab leadership and project management skills into star candidate qualities have an advantage when looking to step into their next position.

See it on Scoop.it (http://www.scoop.it/t/cxannouncements/p/4026732942/2014/08/25/the-transferrable-postdoc) , via CxAnnouncements (http://www.scoop.it/t/cxannouncements)



Complexity and the Human Experience: Modeling Complexity in the Humanities and Social Sciences (edited by Paul A. Youngman & Mirsad Hadzikadic)

    Questions of values, ontologies, ethics, aesthetics, discourse, origins, language, literature, and meaning do not lend themselves readily, or traditionally, to equations, probabilities, and models. However, with the increased adoption of natural science tools in economics, anthropology, and political science?to name only a few social scientific fields highlighted in this volume?quantitative methods in the humanities are becoming more common.

The theory of complexity holds significant promise for better understanding social and human phenomena based on interactions among the participating "agents," whatever they may be: a thought, a person, a conversation, a sentence, or an email. Such systems can exhibit phase transitions, feedback loops, self-organization, and emergent properties. These dynamic systems lend themselves naturally to the kind of analysis made possible by models and simulations developed with complex science tools. This volume offers a tour of quantitative analyses, models, and simulations of humanities and social science phenomena that have been historically the purview of qualitative methods.



See it on Scoop.it (http://www.scoop.it/t/cxbooks/p/4026334654/2014/08/25/complexity-and-the-human-experience-modeling-complexity-in-the-humanities-and-social-sciences-edited-by-paul-a-youngman-mirsad-hadzikadic) , via CxBooks (http://www.scoop.it/t/cxbooks)



==============================================
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Founding Editor: Gottfried Mayer.
Editor-in-Chief: Carlos Gershenson.

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