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

   Barry Wellman

    A vision is just a vision if it's only in your head
    Step by step, link by link, putting it together
   NetLab Network                 FRSC                      INSNA Founder           twitter: @barrywellman
   NETWORKED: The New Social Operating System  Lee Rainie & Barry Wellman

---------- Forwarded message ----------
Date: Mon, 12 Sep 2016 11:04:16 +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

Fundamental structures of dynamic social networks

    We study the dynamic network of real world person-to-person 
interactions between approximately 1,000 individuals with 5-min resolution 
across several months. There is currently no coherent theoretical 
framework for summarizing the tens of thousands of interactions per day in 
this complex network, but here we show that at the right temporal 
resolution, social groups can be identified directly. We outline and 
validate a framework that enables us to study the statistical properties 
of individual social events as well as series of meetings across weeks and 
months. Representing the dynamic network as sequences of such meetings 
reduces the complexity of the system dramatically. We illustrate the 
usefulness of the framework by investigating the predictability of human 
social activity.

Fundamental structures of dynamic social networks
Vedran Sekara, Arkadiusz Stopczynski, and Sune Lehmann

PNAS vol. 113 no. 36

Source: (

Symmetric States Requiring System Asymmetry

Spontaneous synchronization has long served as a paradigm for behavioral 
uniformity that can emerge from interactions in complex systems. When the 
interacting entities are identical and their coupling patterns are also 
identical, the complete synchronization of the entire network is the state 
inheriting the system symmetry. As in other systems subject to symmetry 
breaking, such symmetric states are not always stable. Here, we report on 
the discovery of the converse of symmetry breaking’’the scenario in which 
complete synchronization is not stable for identically coupled identical 
oscillators but becomes stable when, and only when, the oscillator 
parameters are judiciously tuned to nonidentical values, thereby breaking 
the system symmetry to preserve the state symmetry. Aside from 
demonstrating that diversity can facilitate and even be required for 
uniformity and consensus, this suggests a mechanism for convergent forms 
of pattern formation in which initially asymmetric patterns evolve into 
symmetric ones.

Symmetric States Requiring System Asymmetry
Takashi Nishikawa and Adilson E. Motter
Phys. Rev. Lett. 117, 114101

Source: (

See Also: Synopsis: Diversity Breeds Conformity (

From Community Detection to Community Deception

    The community deception problem is about how to hide a target community 
C from community detection algorithms. The need for deception emerges 
whenever a group of entities (e.g., activists, police enforcements) want 
to cooperate while concealing their existence as a community. In this 
paper we introduce and formalize the community deception problem. To solve 
this problem, we describe algorithms that carefully rewire the connections 
of C's members. We experimentally show how several existing community 
detection algorithms can be deceived, and quantify the level of deception 
by introducing a deception score. We believe that our study is intriguing 
since, while showing how deception can be realized it raises awareness for 
the design of novel detection algorithms robust to deception techniques.

From Community Detection to Community Deception
Valeria Fionda, Giuseppe Pirrņ

Source: (

The  C .  elegans  Connectome Consists of Homogenous Circuits with Defined Functional Roles

How can we understand the function of gigantic complex networks (e.g. the 
brain) based on connectivity data alone? We use the available full 
connectome of a nematode and apply new approaches to find that the neural 
network is made of structurally homogeneous neural circuits. These sets of 
neurons also appear in defined regions of the network where they may 
provide valuable functional roles such as signal integration and 
synchronization. Moreover, if we redraw the network considering these 
homogeneous sets alone, we reveal a simplified network layout that is 
intuitive to understand. As connectome data of higher brain systems are 
soon to be released our novel approaches can be immediately applied to 
studying these complex systems.

Azulay A, Itskovits E, Zaslaver A (2016) The C. elegans Connectome Consists of Homogenous Circuits with Defined Functional Roles. PLoS Comput Biol 12(9): e1005021. doi:10.1371/journal.pcbi.1005021

Source: (

Untangling the role of diverse social dimensions in the diffusion of microfinance

    Ties between individuals on a social networks can represent different 
dimensions of interactions, and the spreading of information and 
innovations on these networks could potentially be driven by some 
dimensions more than by others. In this paper we investigate this issue by 
studying the diffusion of microfinance within rural India villages and 
accounting for the whole multilayer structure of the underlying social 
networks. We define a new measure of node centrality, diffusion 
versatility, and show that this is a better predictor of microfinance 
participation rate than previously introduced measures defined on 
aggregated single-layer social networks. Moreover, we untangle the role 
played by each social dimension and find that the most prominent role is 
played by the nodes that are central on layers concerned with trust, 
shedding new light on the key triggers of the diffusion of microfinance.

Untangling the role of diverse social dimensions in the diffusion of microfinance
Elisa Omodei, Alex Arenas

Source: (

The Social Dynamics of Language Change in Online Networks

    Language change is a complex social phenomenon, revealing pathways of 
communication and sociocultural influence. But, while language change has 
long been a topic of study in sociolinguistics, traditional linguistic 
research methods rely on circumstantial evidence, estimating the direction 
of change from differences between older and younger speakers. In this 
paper, we use a data set of several million Twitter users to track 
language changes in progress. First, we show that language change can be 
viewed as a form of social influence: we observe complex contagion for 
phonetic spellings and "netspeak" abbreviations (e.g., lol), but not for 
older dialect markers from spoken language. Next, we test whether specific 
types of social network connections are more influential than others, 
using a parametric Hawkes process model. We find that tie strength plays 
an important role: densely embedded social ties are significantly better 
conduits of linguistic influence. Geographic locality appears to play a 
more limited role: we find relatively little evidence to support the 
hypothesis that individuals are more influenced by geographically local 
social ties, even in their usage of geographical dialect markers.

The Social Dynamics of Language Change in Online Networks
Rahul Goel, Sandeep Soni, Naman Goyal, John Paparrizos, Hanna Wallach, Fernando Diaz, Jacob Eisenstein

Source: (

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 ( ) and using the "Suggest" button.

SOCNET is a service of INSNA, the professional association for social
network researchers ( To unsubscribe, send
an email message to [log in to unmask] containing the line
UNSUBSCRIBE SOCNET in the body of the message.