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SOCNET  January 2015

SOCNET January 2015

Subject:

[comdig] Latest Complexity Digest Posts (fwd)

From:

Barry Wellman <[log in to unmask]>

Reply-To:

Barry Wellman <[log in to unmask]>

Date:

Thu, 29 Jan 2015 09:24:27 -0500

Content-Type:

MULTIPART/MIXED

Parts/Attachments:

Parts/Attachments

TEXT/PLAIN (189 lines)

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


selected

   Barry Wellman
  _______________________________________________________________________
   FRSC		              NetLab Network              INSNA Founder
   Dept of Communication & New Media    National University of Singapore
   University of Toronto                                  Toronto Canada
   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, 26 Jan 2015 16:16:31 -0600
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



Simple model for the Darwinian transition in early evolution

    See it on Scoop.it (http://www.scoop.it/t/papers/p/4035774987/2015/01/25/simple-model-for-the-darwinian-transition-in-early-evolution) , via Papers (http://www.scoop.it/t/papers)



Degeneracy: Demystifying and destigmatizing a core concept in systems biology

    Often relegated to the methods section of genetic research articles, the term   degeneracy   is regularly misunderstood and its theoretical significance widely understated. Degeneracy describes the ability of different structures to be conditionally interchangeable in their contribution to system functions. Frequently mislabeled redundancy, degeneracy refers to structural variation whereas redundancy refers to structural duplication. Sources of degeneracy include, but are not limited to, (1) duplicate structures that differentiate yet remain isofunctional, (2) unrelated isofunctional structures that are dispersed endogenously or exogenously, (3) variable arrangements of interacting structures that achieve the same output through multiple pathways, and (4) parcellation of a structure into subunits that can still variably perform the same initial function. The ability to perform the same function by drawing upon an array of dissimilar structures contributes advantageously to the
integrity of a system. Drawing attention to the heterogeneous construction of living systems by highlighting the concept of degeneracy valuably enhances the ways scientists think about self-organization, robustness, and complexity. Labels in science, however, can sometimes be misleading. In scientific nomenclature, the word   degeneracy   has calamitous proximity to the word   degeneration   used by pathologists and the shunned theory of degeneration once promoted by eugenicists. This article disentangles the concept of degeneracy from its close etymological siblings and offers a brief overview of the historical and contemporary understandings of degeneracy in science. Distinguishing the importance of degeneracy will hopefully allow systems theorists to more strategically operationally conceptualize the distributed intersecting networks that comprise complex living systems.

Degeneracy: Demystifying and destigmatizing a core concept in systems biology
Paul H. Mason

Complexity
Volume 20, Issue 3, pages 12  21, January/February 2015

http://dx.doi.org/10.1002/cplx.21534

See it on Scoop.it (http://www.scoop.it/t/papers/p/4035856552/2015/01/23/degeneracy-demystifying-and-destigmatizing-a-core-concept-in-systems-biology) , via Papers (http://www.scoop.it/t/papers)



All in the (bigger) family

    The next time you are about to dig into a freshly steamed lobster for dinner, think   cockroach,   or better yet,   dragonfly.   A decade of genetic data and other evidence has persuaded most researchers that insects and crustaceans, long considered widely separated branches of the arthropod family tree, actually belong together. Now they are exploring the consequences of the revision, which traces insect ancestry to certain crustaceans.   When I think about traits in insects, I now have a context for where they came from,   says Jon Harrison, an evolutionary physiologist at Arizona State University, Tempe, who has spent 25 years investigating insect respiration.   It's a total change.  

All in the (bigger) family
Elizabeth Pennisi

Science 16 January 2015:
Vol. 347 no. 6219 pp. 220-221
http://dx.doi.org/10.1126/science.347.6219.220
Complexity Digest's insight:

Let us hope that this revision promotes insectivorism: http://go.ted.com/suG

See it on Scoop.it (http://www.scoop.it/t/papers/p/4035855933/2015/01/23/all-in-the-bigger-family) , via Papers (http://www.scoop.it/t/papers)

Development, information and social connectivity in C˘te d'Ivoire

    Understanding human socioeconomic development has proven to be one of the most difficult and persistent problems in science and policy. Traditional policy has often attempted to promote human development through infrastructure and the delivery of services, but the link between these engineered systems and the complexity of human socioeconomic behavior remains poorly understood. Recent research suggests that the key to socioeconomic progress lies in the development of processes whereby new information is created by individuals and organizations and embedded in the structure of social networks at a diverse set of scales, from nations to cities to firms. Here, we formalize these ideas in terms of network theory  namely the spatial network of mobile phone communications in C˘te d  Ivoire--to show how incipient socioeconomic connectivity may constitute a general obstacle to development. Inspired by recent progress in the theory of cities as complex systems, we then propose a set of
tests for these theories using telecommunications network data and describe how telecommunication services may generally help promote socioeconomic development.

Development, information and social connectivity in C˘te d  Ivoire
Clio Andris and Luis MA Bettencourt

Infrastructure Complexity 2014, 1:1  http://dx.doi.org/10.1186/s40551-014-0001-4

See it on Scoop.it (http://www.scoop.it/t/papers/p/4035780303/2015/01/22/development-information-and-social-connectivity-in-cote-d-ivoire) , via Papers (http://www.scoop.it/t/papers)


Human-Data Interaction: The Human Face of the Data-Driven Society

    The increasing generation and collection of personal data has created a complex ecosystem, often collaborative but sometimes combative, around companies and individuals engaging in the use of these data. We propose that the interactions between these agents warrants a new topic of study: Human-Data Interaction (HDI). In this paper we discuss how HDI sits at the intersection of various disciplines, including computer science, statistics, sociology, psychology and behavioural economics. We expose the challenges that HDI raises, organised into three core themes of legibility, agency and negotiability, and we present the HDI agenda to open up a dialogue amongst interested parties in the personal and big data ecosystems.

Human-Data Interaction: The Human Face of the Data-Driven Society
Richard Mortier, Hamed Haddadi, Tristan Henderson, Derek McAuley, Jon Crowcroft

http://arxiv.org/abs/1412.6159

See it on Scoop.it (http://www.scoop.it/t/papers/p/4035777637/2015/01/22/human-data-interaction-the-human-face-of-the-data-driven-society) , via Papers (http://www.scoop.it/t/papers)



NETWORKED MINDS: Where human evolution is heading

    Having studied the technological and social forces shaping our societies, we are now turning to the evolutionary forces. Among the millions of species on earth, humans are truly unique.
What is the recipe of our success? What makes us special? How do we decide? How will we further evolve? What will our role be, when algorithms, computers, machines, and robots are getting ever more powerful? How will our societies change?

http://futurict.blogspot.ie/2014/12/networked-minds-where-human-evolution.html

See it on Scoop.it (http://www.scoop.it/t/papers/p/4035636397/2015/01/22/networked-minds-where-human-evolution-is-heading) , via Papers (http://www.scoop.it/t/papers)



A Unifying Theory for Scaling Laws of Human Populations

    The spatial distribution of people exhibits clustering across a wide range of scales, from household to continental  scales. Empirical data indicates simple power-law scalings for the size distribution of cities (known as Zipf's law), the geographic distribution of friends, and the population density fluctuations as a function of scale. We derive a simple statistical model that explains all of these scaling laws based on a single unifying principle involving the random spatial growth of clusters of people on all scales. The model makes important new predictions for the spread of diseases and other social phenomena.

A Unifying Theory for Scaling Laws of Human Populations
Henry W. Lin, Abraham Loeb

http://arxiv.org/abs/1501.00738

See it on Scoop.it (http://www.scoop.it/t/papers/p/4035777622/2015/01/22/a-unifying-theory-for-scaling-laws-of-human-populations) , via Papers (http://www.scoop.it/t/papers)



Estimating Food Consumption and Poverty Indices with Mobile Phone Data

    Recent studies have shown the value of mobile phone data to tackle problems related to economic development and humanitarian action. In this research, we assess the suitability of indicators derived from mobile phone data as a proxy for food security indicators. We compare the measures extracted from call detail records and airtime credit purchases to the results of a nationwide household survey conducted at the same time. Results show high correlations (> .8) between mobile phone data derived indicators and several relevant food security variables such as expenditure on food or vegetable consumption. This correspondence suggests that, in the future, proxies derived from mobile phone data could be used to provide valuable up-to-date operational information on food security throughout low and middle income countries.

Estimating Food Consumption and Poverty Indices with Mobile Phone Data
Adeline Decuyper, Alex Rutherford, Amit Wadhwa, Jean-Martin Bauer, Gautier Krings, Thoralf Gutierrez, Vincent D. Blondel, Miguel A. Luengo-Oroz

http://arxiv.org/abs/1412.2595

See it on Scoop.it (http://www.scoop.it/t/papers/p/4035778502/2015/01/22/estimating-food-consumption-and-poverty-indices-with-mobile-phone-data) , via Papers (http://www.scoop.it/t/papers)



Mason A. Porter: Cascades and Social influence on networks

    I discuss "simple" dynamical systems on networks and examine how network structure affects dynamics of processes running on top of networks. I'll give an introduction to the idea of social ("complex") contagions, and I'll present a model for multi-stage complex contagions in which fanatics produce greater influence than mere followers.  I'll also briefly discuss the use of ideas from topics like persistent homology to examine wavefront propagation versus the appearance of new contagion clusters, and I'll present a model (without network structure) for the adoption of applications on Facebook. The last family of models illustrates how very different time-dependent dynamics can produce quantitatively similar long-time behavior, which poses both very serious challenges and exciting opportunities for the modeling of complex systems.

See it on Scoop.it (http://www.scoop.it/t/talks/p/4035773490/2015/01/22/mason-a-porter-cascades-and-social-influence-on-networks) , via Talks (http://www.scoop.it/t/talks)



SOCIAL FORCES: Revealing the causes of success or disaster

    We have seen that self-organizing systems can be very effective and efficient, but their macro-level behavior crucially depends on the interaction rules, interaction strength, and institutional settings. To get things right, it's important to understand the factors that drive the dynamics of the system.

http://futurict.blogspot.ie/2014/12/social-forces-revealing-causes-of.html

See it on Scoop.it (http://www.scoop.it/t/papers/p/4035632752/2015/01/20/social-forces-revealing-the-causes-of-success-or-disaster) , via Papers (http://www.scoop.it/t/papers)



The multilayer temporal network of public transport in Great Britain
Riccardo Gallotti & Marc Barthelemy

Scientific Data, Published online: 6 January 2015; | http://dx.doi.org/10.1038/sdata.2014.56

See it on Scoop.it (http://www.scoop.it/t/papers/p/4034992193/2015/01/19/the-multilayer-temporal-network-of-public-transport-in-great-britain) , via Papers (http://www.scoop.it/t/papers)



Computational fact checking from knowledge networks

    Traditional fact checking by expert journalists cannot keep up with the enormous volume of information that is now generated online. Computational fact checking may significantly enhance our ability to evaluate the veracity of dubious information. Here we show that the complexities of human fact checking can be approximated quite well by finding the shortest path between concept nodes under properly defined semantic proximity metrics on knowledge graphs. Framed as a network problem this approach is feasible with efficient computational techniques. We evaluate this approach by examining tens of thousands of claims related to history, entertainment, geography, and biographical information using a public knowledge graph extracted from Wikipedia. Statements independently known to be true consistently receive higher support via our method than do false ones. These findings represent a significant step toward scalable computational fact-checking methods that may one day mitigate
the spread of harmful misinformation.

Computational fact checking from knowledge networks
Giovanni Luca Ciampaglia, Prashant Shiralkar, Luis M. Rocha, Johan Bollen, Filippo Menczer, Alessandro Flammini

http://arxiv.org/abs/1501.03471

See it on Scoop.it (http://www.scoop.it/t/papers/p/4035340873/2015/01/19/computational-fact-checking-from-knowledge-networks) , via Papers (http://www.scoop.it/t/papers)



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

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