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SOCNET  August 2016

SOCNET August 2016

Subject:

selected Latest Complexity Digest Posts (fwd)

From:

Barry Wellman <[log in to unmask]>

Reply-To:

Barry Wellman <[log in to unmask]>

Date:

Mon, 15 Aug 2016 09:40:08 -0400

Content-Type:

MULTIPART/MIXED

Parts/Attachments:

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TEXT/PLAIN (340 lines)

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

Thanks to the person who wrote that he finds these selections useful.
Would appreciate hearing from others. And if you have even more time, 
which one(s) you found useful.

Grooming is importnat. (I'm reading a book on Baboons now)

   Barry Wellman

    A vision is just a vision if it's only in your head
    Step by step, link by link, putting it together
                  Streisand/Sondheim
  _______________________________________________________________________
   NetLab Network                 FRSC                      INSNA Founder
   http://www.chass.utoronto.ca/~wellman           twitter: @barrywellman
   NETWORKED: The New Social Operating System  Lee Rainie & Barry Wellman
                        http://amzn.to/zXZg39
   _______________________________________________________________________


---------- Forwarded message ----------
Date: Mon, 15 Aug 2016 11:04:47 +0000
From: "[utf-8] Complexity Digest" <[log in to unmask]>
Reply-To: [log in to unmask]
To: "[utf-8] Barry" <[log in to unmask]>
Subject: [utf-8] Latest Complexity Digest Posts

Learn about the latest and greatest related to complex systems research. More at http://unam.us4.list-manage1.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=f73e85e7a3&e=55e25a0e3e



Higher-order organization of complex networks

    Networks are a fundamental tool for understanding and modeling complex 
systems in physics, biology, neuroscience, engineering, and social 
science. Many networks are known to exhibit rich, lower-order connectivity 
patterns that can be captured at the level of individual nodes and edges. 
However, higher-order organization of complex networks  at the level of 
small network subgraphs  remains largely unknown. Here, we develop a 
generalized framework for clustering networks on the basis of higher-order 
connectivity patterns. This framework provides mathematical guarantees on 
the optimality of obtained clusters and scales to networks with billions 
of edges. The framework reveals higher-order organization in a number of 
networks, including information propagation units in neuronal networks and 
hub structure in transportation networks. Results show that networks 
exhibit rich higher-order organizational structures that are exposed by 
clustering based on higher-order connectivity patterns.


Higher-order organization of complex networks
Austin R. Benson, David F. Gleich, Jure Leskovec

Science  08 Jul 2016:
Vol. 353, Issue 6295, pp. 163-166
http://unam.us4.list-manage1.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=bfa72050ec&e=55e25a0e3e

See it on Scoop.it (http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=ddcd515b56&e=55e25a0e3e) , via Papers (http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=2527eb36c7&e=55e25a0e3e)



Extended Intelligence

    We propose a kind of Extended Intelligence (EI), understanding 
intelligence as a fundamentally distributed phenomenon. As we develop 
increasingly powerful tools to process information and network that 
processing, aren  t we just adding new pieces to the EI that every actor 
in the network is a part of?


Extended Intelligence

Joichi Ito
[BW: He's the head of MIT's Media Lab, among other htings]

Journal of Design and Science

http://unam.us4.list-manage2.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=55e112fb88&e=55e25a0e3e

See it on Scoop.it (http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=9c2b85236b&e=55e25a0e3e) , via Papers (http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=aa3a3838d3&e=55e25a0e3e)



Microbiology: Mob rule

    It seems that, instead of being self-contained, the contents of the 
human gene kit are generously supplemented by a plethora of extraneous 
components. These riches come from the topsy-turvy world of 
microorganisms, symbionts whose products bolt onto the more modest 
collection furnished by their hosts. The implications of this extra 
informational dimension, and how it interweaves with our genes, are 
explored in four new books.


   I Contain Multitudes: The Microbes Within Us and a Grander View of Life.   Ed Yong
   The Human Superorganism: How the Microbiome Is Revolutionizing the Pursuit of a Healthy Life.   Rodney Dietert
   This Is Your Brain on Parasites: How Tiny Creatures Manipulate Our Behavior and Shape Society.   Kathleen McAuliffe
   The Mind  Gut Connection: How the Hidden Conversation Within Our Bodies Impacts Our Mood, Our Choices, and Our Overall Health  . Emeran Mayer


Microbiology: Mob rule
Adrian Woolfson
Nature 536, 146  147 (11 August 2016) http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=c478c021ac&e=55e25a0e3e

See it on Scoop.it (http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=26f2c731d3&e=55e25a0e3e) , via CxBooks (http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=c6ad03237d&e=55e25a0e3e)



A multilayer approach to multiplexity and link prediction in online geo-social networks

    Online social systems are multiplex in nature as multiple links may 
exist between the same two users across different social media. In this 
work, we study the geo-social properties of multiplex links, spanning more 
than one social network and apply their structural and interaction 
features to the problem of link prediction across social networking 
services. Exploring the intersection of two popular online platforms - 
Twitter and location-based social network Foursquare - we represent the 
two together as a composite multilayer online social network, where each 
platform represents a layer in the network. We find that pairs of users 
connected on both services, have greater neighbourhood similarity and are 
more similar in terms of their social and spatial properties on both 
platforms in comparison with pairs who are connected on just one of the 
social networks. Our evaluation, which aims to shed light on the 
implications of multiplexity for the link generation process, shows that 
we can successfully predict links across social networking services. In 
addition, we also show how combining information from multiple 
heterogeneous networks in a multilayer configuration can provide new 
insights into user interactions on online social networks, and can 
significantly improve link prediction systems with valuable applications 
to social bootstrapping and friend recommendations.


A multilayer approach to multiplexity and link prediction in online geo-social networks
Hristova D, Noulas A, Brown C, Musolesi M, Mascolo C
EPJ Data Science 2016, 5 :24 (26 July 2016)

http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=a2f28bfffb&e=55e25a0e3e

See it on Scoop.it (http://unam.us4.list-manage2.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=bc2ea739f8&e=55e25a0e3e) , via Papers (http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=ac6952044b&e=55e25a0e3e)


Interdisciplinary research has consistently lower funding success

    Interdisciplinary research is widely considered a hothouse for 
innovation, and the only plausible approach to complex problems such as 
climate change1, 2. One barrier to interdisciplinary research is the 
widespread perception that interdisciplinary projects are less likely to 
be funded than those with a narrower focus3, 4. However, this commonly 
held belief has been difficult to evaluate objectively, partly because of 
lack of a comparable, quantitative measure of degree of 
interdisciplinarity that can be applied to funding application data1. Here 
we compare the degree to which research proposals span disparate fields by 
using a biodiversity metric that captures the relative representation of 
different fields (balance) and their degree of difference (disparity). The 
Australian Research Council  s Discovery Programme provides an ideal test 
case, because a single annual nationwide competitive grants scheme covers 
fundamental research in all disciplines, including arts, humanities and 
sciences. Using data on all 18,476 proposals submitted to the scheme over 
5 consecutive years, including successful and unsuccessful applications, 
we show that the greater the degree of interdisciplinarity, the lower the 
probability of being funded. The negative impact of interdisciplinarity is 
significant even when number of collaborators, primary research field and 
type of institution are taken into account. This is the first broad-scale 
quantitative assessment of success rates of interdisciplinary research 
proposals. The interdisciplinary distance metric allows efficient 
evaluation of trends in research funding, and could be used to identify 
proposals that require assessment strategies appropriate to 
interdisciplinary research5.


Interdisciplinary research has consistently lower funding success
Lindell Bromham, Russell Dinnage & Xia Hua

Nature 534, 684  687 (30 June 2016) http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=04411755df&e=55e25a0e3e

See it on Scoop.it (http://unam.us4.list-manage2.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=95cc634bee&e=55e25a0e3e) , via Papers (http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=7731fcbadb&e=55e25a0e3e)



How Structured Is the Entangled Bank? The Surprisingly Simple Organization of Multiplex Ecological Networks Leads to Increased Persistence and Resilience

    Within an ecosystem, species interact with each other in many different 
ways, including predation, competition, and facilitation, and this can be 
modelled as a network of multiple interaction types. The variety of 
interaction types that link species to each other has long been recognized 
but has rarely been synthesized for entire multi-species ecosystems. Here, 
we leverage a unique marine ecological network that integrates thousands 
of trophic and non-trophic interactions. We show that, despite its 
multidimensional complexity, this ecological network collapses into a 
small set of   functional groups,   i.e., groups of species that resemble 
each other in the way they interact with others in their combined trophic 
and non-trophic interactions. These groups are taxonomically coherent and 
predictable by species attributes. Moreover, dynamic simulations suggest 
that the way the different interaction types relate to each other allows 
for higher species persistence and higher total biomass than is expected 
by chance alone, and that this tends to promote a higher robustness to 
extinctions. Our results will help to guide future empirical studies and 
to develop a more general theory of the dynamics of complex ecological 
systems.


KÚfi S, Miele V, Wieters EA, Navarrete SA, Berlow EL (2016) How Structured Is the Entangled Bank? The Surprisingly Simple Organization of Multiplex Ecological Networks Leads to Increased Persistence and Resilience. PLoS Biol 14(8): e1002527. http://unam.us4.list-manage2.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=61ccaff035&e=55e25a0e3e

See it on Scoop.it (http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=02426dabe0&e=55e25a0e3e) , via Papers (http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=e3093b6b97&e=55e25a0e3e)

Extracting Hidden Hierarchies in 3D Distribution Networks

    Complex networks like neural maps and the internet are characterized by 
a large number of connected nodes. A new algorithm shows how 
three-dimensional networks can be computationally simplified by tiling an 
abstract surface.


Extracting Hidden Hierarchies in 3D Distribution Networks
Carl D. Modes, Marcelo O. Magnasco, and Eleni Katifori
Phys. Rev. X 6, 031009 (2016)

http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=ad118f97d4&e=55e25a0e3e

See it on Scoop.it (http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=f8057d545e&e=55e25a0e3e) , via Papers (http://unam.us4.list-manage1.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=c275f72cb8&e=55e25a0e3e)


The strength of long ties and the weakness of strong ties: Knowledge diffusion through supply chain networks

      Examines the effects of supply chains on productivity and innovation 
through knowledge diffusion.   Ties with distant suppliers benefit more 
than ties with neighboring suppliers.   Ties with neighboring clients 
benefit more than ties with distant clients.   Density of a firm's ego 
network has a negative effect.   These results suggest that access to 
diversified is important for knowledge diffusion.


The strength of long ties and the weakness of strong ties: Knowledge diffusion through supply chain networks   
Yasuyuki Todoa, , , Petr Matousb, , Hiroyasu Inoue

Research Policy

http://unam.us4.list-manage1.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=8f262d0ec4&e=55e25a0e3e

See it on Scoop.it (http://unam.us4.list-manage2.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=920739b310&e=55e25a0e3e) , via Papers (http://unam.us4.list-manage1.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=c3f43678a7&e=55e25a0e3e)


Fractal dimension versus computational complexity

    Complexity measures are designed to capture complex behavior and 
quantify *how* complex, according to that measure, that particular 
behavior is. It can be expected that different complexity measures from 
possibly entirely different fields are related to each other in a 
non-trivial fashion. Here we study small Turing machines (TMs) with two 
symbols, and two and three states. For any particular such machine    and 
any particular input x we consider what we call the 'space-time' diagram 
which is the collection of consecutive tape configurations of the 
computation   (x). In our setting, we define fractal dimension of a Turing 
machine as the limiting fractal dimension of the corresponding space-time 
diagram. It turns out that there is a very strong relation between the 
fractal dimension of a Turing machine of the above-specified type and its 
runtime complexity. In particular, a TM with three states and two colors 
runs in at most linear time iff its dimension is 2, and its dimension is 1 
iff it runs in super-polynomial time and it uses polynomial space. If a TM 
runs in time O(x^n) we have empirically verified that the corresponding 
dimension is (n+1)/n, a result that we can only partially prove. We find 
the results presented here remarkable because they relate two completely 
different complexity measures: the geometrical fractal dimension on the 
one side versus the time complexity of a computation on the other side.


Fractal dimension versus computational complexity
Joost J. Joosten, Fernando Soler-Toscano, Hector Zenil

http://unam.us4.list-manage2.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=19870b0214&e=55e25a0e3e

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Postdoctoral and Student/Predoctoral Research Positions @NECSI

    The New England Complex Systems Institute has funding for postdoctoral and predoctoral research appointments. We are looking for outstanding applicants interested in retrieving and analyzing unstructured patterns of information from large datasets. Areas of application include:

- Human dynamics
- Socio-economic systems
- Medical records

Training in physics, mathematics or computer science is preferred but not required. We value strong writing abilities, and interest in:

- Big data analytics
- Multiscale representations
- Network science
To apply please visit:
http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=24ea25e49a&e=55e25a0e3e

See it on Scoop.it (http://unam.us4.list-manage1.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=7d86c88f98&e=55e25a0e3e) , via CxAnnouncements (http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=21dcbad1a0&e=55e25a0e3e)



On the Self-Organizing Origins of Agency

    The question of agency and directedness in living systems has puzzled 
philosophers and scientists for centuries. What principles and mechanisms 
underlie the emergence of agency? Analysis and dynamical modeling of 
experiments on human infants suggest that the birth of agency is due to a 
eureka-like, pattern-forming phase transition in which the infant suddenly 
realizes it can make things happen in the world. The main mechanism 
involves positive feedback: when the baby's initially spontaneous 
movements cause the world to change, their perceived consequences have a 
sudden and sustained amplifying effect on the baby's further actions. The 
baby discovers itself as a causal agent. Some implications of this theory 
are discussed.


On the Self-Organizing Origins of Agency
J.A. Scott Kelso

Trends in Cognitive Science

Volume 20, Issue 7, p490  499, July 2016

http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=1455a8ccf0&e=55e25a0e3e

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==============================================
Sponsored by the Complex Systems Society.
Founding Editor: Gottfried Mayer.
Editor-in-Chief: Carlos Gershenson.

You can contribute to Complexity Digest selecting one of our topics (http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=2dadc5bb35&e=55e25a0e3e ) and using the "Suggest" button.
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