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Subject: [comdig] Latest Complexity Digest Posts (fwd)
From: Barry Wellman <[log in to unmask]>
Reply-To:Barry Wellman <[log in to unmask]>
Date:Tue, 5 Aug 2014 18:34:35 -0400

TEXT/PLAIN (168 lines)

*****  To join INSNA, visit  *****


   Barry Wellman
   FRSC		              NetLab Network              INSNA Founder
                      Faculty of Information (iSchool)
   University of Toronto                          Toronto Canada M5S 3G6          twitter: @barrywellman
   NETWORKED:The New Social Operating System. Lee Rainie & Barry Wellman
   MIT Press        Print $15  Kindle $9

---------- Forwarded message ----------
Date: Tue, 5 Aug 2014 16:45:19 -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

A network framework of cultural history

    The emergent processes driving cultural history are a product of complex interactions among large numbers of individuals, determined by difficult-to-quantify historical conditions. To characterize these processes, we have reconstructed aggregate intellectual mobility over two millennia through the birth and death locations of more than 150,000 notable individuals. The tools of network and complexity theory were then used to identify characteristic statistical patterns and determine the cultural and historical relevance of deviations. The resulting network of locations provides a macroscopic perspective of cultural history, which helps us to retrace cultural narratives of Europe and North America using large-scale visualization and quantitative dynamical tools and to derive historical trends of cultural centers beyond the scope of specific events or narrow time intervals.

A network framework of cultural historyMaximilian Schich ( , Chaoming Song ( ,  Yong-Yeol Ahn ( ,  Alexander Mirsky ( , Mauro Martino ( , Albert-László Barabási ( , Dirk Helbing (

Science 1 August 2014:
Vol. 345 no. 6196 pp. 558-562

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On the structural stability of mutualistic systems

    Structural stability has played a major role in several fields such as evolutionary developmental biology, in which it has brought the view that some morphological structures are more common than others because they are compatible with a wider range of developmental conditions. In community ecology, structural stability is the sort of framework needed to study the consequences of global environmental change˙˙by definition, large and directional˙˙on species coexistence. Structural stability will serve to assess both the range of variability a given community can withstand and why some community patterns are more widespread than others.

On the structural stability of mutualistic systems
Rudolf P. Rohr, Serguei Saavedra, Jordi Bascompte

Science 25 July 2014:
Vol. 345 no. 6195

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Stigmergy as a Universal Coordination Mechanism: components, varieties and applications

    The concept of stigmergy has been used to analyze self-organizing activities in an ever-widening range of domains, from social insects via robotics and social media to human society. Yet, it is still poorly understood, and as such its full power remains underappreciated. The present paper clarifies the issue by defining stigmergy as a mechanism of indirect coordination in which the trace left by an action in a medium stimulates a subsequent action. It then analyses the fundamental components of the definition: action, agent, medium, trace and coordination. Stigmergy enables complex, coordinated activity without any need for planning, control, communication, simultaneous presence, or even mutual awareness. This makes the concept applicable to a very broad variety of cases, from chemical reactions to individual cognition and Internet-supported collaboration in Wikipedia.  The paper classifies different varieties of stigmergy according to general aspects (number of agents,
scope, persistence, sematectonic vs. marker-based, and quantitative vs. qualitative), while emphasizing the fundamental continuity between these cases. This continuity can be understood from a non-linear, self-organizing dynamic that lets more complex forms of coordination evolve out of simpler ones. The paper concludes with two specifically human applications in cognition and cooperation, suggesting that without stigmergy these phenomena may never have evolved.

Heylighen, F. (2015). Stigmergy as a Universal Coordination Mechanism: components, varieties and applications. To appear in T. Lewis & L. Marsh (Eds.), Human Stigmergy: Theoretical Developments and New Applications, Studies in Applied Philosophy, Epistemology and Rational Ethics. Springer.

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From Dyson to Hopfield: Processing on hierarchical networks

    We consider statistical-mechanical models for spin systems built on hierarchical structures, which provide a simple example of non-mean-field framework. We show that the coupling decay with spin distance can give rise to peculiar features and phase diagrams much richer that their mean-field counterpart. In particular, we consider the Dyson model, mimicking ferromagnetism in lattices, and we prove the existence of a number of meta-stabilities, beyond the ordered state, which get stable in the thermodynamic limit. Such a feature is retained when the hierarchical structure is coupled with the Hebb rule for learning, hence mimicking the modular architecture of neurons, and gives rise to an associative network able to perform both as a serial processor as well as a parallel processor, depending crucially on the external stimuli and on the rate of interaction decay with distance; however, those emergent multitasking features reduce the network capacity with respect to the
mean-field counterpart. The analysis is accomplished through statistical mechanics, graph theory, signal-to-noise technique and numerical simulations in full consistency. Our results shed light on the biological complexity shown by real networks, and suggest future directions for understanding more realistic models.

From Dyson to Hopfield: Processing on hierarchical networks
Elena Agliari, Adriano Barra, Andrea Galluzzi, Francesco Guerra, Daniele Tantari, Flavia Tavani

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Self-organization on social media: endo-exo bursts and baseline fluctuations

    A salient dynamic property of social media is bursting behavior. In this paper, we study bursting behavior in terms of the temporal relation between a preceding baseline fluctuation and the successive burst response using a frequency time series of 3,000 keywords on Twitter. We found that there is a fluctuation threshold up to which the burst size increases as the fluctuation increases and that above the threshold, there appears a variety of burst sizes. We call this threshold the critical threshold. Investigating this threshold in relation to endogenous bursts and exogenous bursts based on peak ratio and burst size reveals that the bursts below this threshold are endogenously caused and above this threshold, exogenous bursts emerge. Analysis of the 3,000 keywords shows that all the nouns have both endogenous and exogenous origins of bursts and that each keyword has a critical threshold in the baseline fluctuation value to distinguish between the two. Having a threshold for
an input value for activating the system implies that Twitter is an excitable medium. These findings are useful for characterizing how excitable a keyword is on Twitter and could be used, for example, to predict the response to particular information on social media.

Self-organization on social media: endo-exo bursts and baseline fluctuations

Mizuki Oka, Yasuhiro Hashimoto, Takashi Ikegami

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Null Models for Community Detection in Spatially-Embedded, Temporal Networks

    In the study of networks, it is often insightful to use algorithms to determine mesoscale features such as "community structure", in which densely connected sets of nodes constitute "communities" that have sparse connections to other communities. The most popular way of detecting communities algorithmically is to optimize the quality function known as modularity. When optimizing modularity, one compares the actual connections in a (static or time-dependent) network to the connections obtained from a random-graph ensemble that acts as a null model. The communities are then the sets of nodes that are connected to each other densely relative to what is expected from the null model. Clearly, the process of community detection depends fundamentally on the choice of null model, so it is important to develop and analyze novel null models that take into account appropriate features of the system under study. In this paper, we investigate the effects of using null models that take
incorporate spatial information, and we propose a novel null model based on the radiation model of population spread. We also develop novel synthetic spatial benchmark networks in which the connections between entities are based on distance or flux between nodes, and we compare the performance of both static and time-dependent radiation null models to the standard ("Newman-Girvan") null model for modularity optimization and a recently-proposed gravity null model. In our comparisons, we use both the above synthetic benchmarks and time-dependent correlation networks that we construct using countrywide dengue fever incidence data for Peru. We also evaluate a recently-proposed correlation null model, which was developed specifically for correlation networks that are constructed from time series, on the epidemic-correlation data.

Null Models for Community Detection in Spatially-Embedded, Temporal Networks
Marta Sarzynska, Elizabeth A. Leicht, Gerardo Chowell, Mason A. Porter

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Short-range interaction vs long-range correlation in bird flocks

    We use the maximum entropy method to study how the strength of effective alignment between birds depends on distance. We find in all analyzed flocks that the interaction decays exponentially. Such short-range form is noteworthy, considering that the velocity correlation that is input of the calculation is long-ranged. We use our method to study the directional anisotropy in the alignment interaction and find that the interaction strength along the direction of motion is weaker than in the transverse direction, which may account for the anisotropic spatial distribution of birds observed in natural flocks.

Short-range interaction vs long-range correlation in bird flocks
Andrea Cavagna, Lorenzo Del Castello, Supravat Dey, Irene Giardina, Stefania Melillo, Leonardo Parisi, Massimiliano Viale

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Introduction to Hypernetworks

    A new module on the Étoile Platform, by Jeffrey Johnson

Based on the course presented at the 4th Ph.D. summer School - conference on ˙˙Mathematical Modeling of Complex Systems˙˙, Cultural Foundation ˙˙Kritiki Estia˙˙, 14 ˙˙ 25 July, 2014, Athens.

The modern world is complex beyond human understanding and control. The science of complex systems aims to find new ways of thinking about the many interconnected networks of interaction that defy traditional approaches. Thus far, research into networks has largely been restricted to pairwise relationships represented by links between two nodes.

This course marks a major extension of networks to multidimensional hypernetworks for modeling multi-element relationships, such as companies making up the stock market, the neighborhoods forming a city, people making up committees, divisions making up companies, computers making up the internet, men and machines making up armies, or robots working as teams. This course makes an important contribution to the science of complex systems by: (i) extending network theory to include dynamic relationships between many elements; (ii) providing a mathematical theory able to integrate multilevel dynamics in a coherent way; (iii) providing a new methodological approach to analyze complex systems; and (iv) illustrating the theory with practical examples in the design, management and control of complex systems taken from many areas of application.

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Interview: Prof  Geoffrey West on complexity science

    CLC interviewed Prof. Geoffrey West, Distinguished Professor and Past President of Sante Fe Institute, at the World Cities Summit 2014 on the study of cities in relation to complexity science....

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

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