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Date: Mon, 28 Mar 2016 12:02:48 +0000
From: "[utf-8] Complexity Digest" <[log in to unmask]>
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Subject: [utf-8] Latest Complexity Digest Posts

Learn about the latest and greatest related to complex systems research. More at

Corruption corrupts

    A cross-cultural experiment involving thousands of people worldwide 
shows that the prevalence of rule violations in a society, such as tax 
evasion and fraudulent politics, is detrimental to individuals' intrinsic 

Behavioural economics: Corruption corrupts
Shaul Shalvi
Nature 531, 456˙˙457 (24 March 2016)

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Homophily, influence and the decay of segregation in self-organizing networks

    We study the persistence of network segregation in networks characterized by the co-evolution of vertex attributes and link structures, in particular where individual vertices form linkages on the basis of similarity with other network vertices (homophily), and where vertex attributes diffuse across linkages, making connected vertices more similar over time (influence). A general mathematical model of these processes is used to examine the relative influence of homophily and influence in the maintenance and decay of network segregation in self-organizing networks. While prior work has shown that homophily is capable of producing strong network segregation when attributes are fixed, we show that adding even minute levels of influence is sufficient to overcome the tendency towards segregation even in the presence of relatively strong homophily processes. This result is proven mathematically for all large networks and illustrated through a series of computational simulations
that account for additional network evolution processes. This research contributes to a better theoretical understanding of the conditions under which network segregation and related phenomenon˙˙such as community structure˙˙may emerge, which has implications for the design of interventions that may promote more efficient network structures.

Homophily, influence and the decay of segregation in self-organizing networks

Network Science / Volume 4 / Issue 01 / March 2016, pp 81-116

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Unveiling causal activity of complex networks

    We introduce a novel tool for analyzing complex network dynamics, 
allowing for cascades of causally-related events, which we call causal 
webs (c-webs for short), to be separated from other activity. In the 
context of neural networks, c-webs represent a new, emergent dynamical 
degree of freedom which highlights the effective network connectivity, in 
contrast with the oft-used degrees of freedom, neuronal avalanches. By 
identifying non-causal activity, our method can also be used to 
characterize dynamical disorder in complex networks. Using this method, we 
reveal causally-related activity from experimental data with statistics 
which may support quasicriticality in the brain.

Unveiling causal activity of complex networks
Rashid V. Williams-Garcia, John M. Beggs, Gerardo Ortiz

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How Diversity Makes Us Smarter

    Decades of research by organizational scientists, psychologists, 
sociologists, economists and demographers show that socially diverse 
groups (that is, those with a diversity of race, ethnicity, gender and 
sexual orientation) are more innovative than homogeneous groups. It seems 
obvious that a group of people with diverse individual expertise would be 
better than a homogeneous group at solving complex, nonroutine problems. 
It is less obvious that social diversity should work in the same way˙˙yet 
the science shows that it does. This is not only because people with 
different backgrounds bring new information. Simply interacting with 
individuals who are different forces group members to prepare better, to 
anticipate alternative viewpoints and to expect that reaching consensus 
will take effort.

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The impact of social networks on leadership behaviour

    Dominant streams in leadership literature conceptualise it either as a role within sociopolitical structure or as a behavioural predisposition of agents. In this article, a number of hypotheses are tested via an empirical case study where interaction and affiliation networks across multiple decision experiments are coupled with attribute and psychometric data of the actors.  Findings suggest that in egalitarian political systems, centrality in social networks is directly associated with political success, while in political systems imbued with power inequalities successful actors are idiocentric brokers. The use of attitudinal micro-surveys, psychometric tests, observation and relational surveys is combined for a comprehensive mapping of group dynamics suited to questions of agency.

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INSNA | XXXVI Sunbelt Conference 2016 |


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