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To Each According to its Degree: The Meritocracy and Topocracy of Embedded Markets

To Each According to its Degree: The Meritocracy and Topocracy of Embedded Markets | Papers | Scoop.it

A system is said to be meritocratic if the compensation and power available to individuals is determined by their abilities and merits. A system is topocratic if the compensation and power available to an individual is determined primarily by her position in a network. Here we introduce a model that is perfectly meritocratic for fully connected networks but that becomes topocratic for sparse networks-like the ones in society. In the model, individuals produce and sell content, but also distribute the content produced by others when they belong to the shortest path connecting a buyer and a seller. The production and distribution of content defines two channels of compensation: a meritocratic channel, where individuals are compensated for the content they produce, and a topocratic channel, where individual compensation is based on the number of shortest paths that go through them in the network. We solve the model analytically and show that the distribution of payoffs is meritocratic only if the average degree of the nodes is larger than a root of the total number of nodes. We conclude that, in the light of this model, the sparsity and structure of networks represents a fundamental constraint to the meritocracy of societies.


To Each According to its Degree: The Meritocracy and Topocracy of Embedded Markets
J. Borondo, F. Borondo, C. Rodriguez-Sickert & C. A. Hidalgo

Scientific Reports 4, Article number: 3784 http://dx.doi.org/10.1038/srep03784

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Computer science: The learning machines

Three years ago, researchers at the secretive Google X lab in Mountain View, California, extracted some 10 million still images from YouTube videos and fed them into Google Brain — a network of 1,000 computers programmed to soak up the world much as a human toddler does. After three days looking for recurring patterns, Google Brain decided, all on its own, that there were certain repeating categories it could identify: human faces, human bodies and … cats.

Google Brain's discovery that the Internet is full of cat videos provoked a flurry of jokes from journalists. But it was also a landmark in the resurgence of deep learning: a three-decade-old technique in which massive amounts of data and processing power help computers to crack messy problems that humans solve almost intuitively, from recognizing faces to understanding language.


http://www.nature.com/news/computer-science-the-learning-machines-1.14481

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Open Learning at a Distance: Lessons for Struggling MOOCs

Free education is changing how people think about learning online. The rise of Massive Open Online Courses (MOOCs) (1) shows that large numbers of learners can be reached. It also raises questions as to how effectively they support learning (2). There is a timeliness in the introduction of MOOCs, reflecting the right combination of online systems, interest from good teachers in reaching more learners, and banks of digital resources, predicted as a “perfect storm of innovation” (3). However, learning at scale, at a distance, is not a new phenomenon. Seeing MOOCs narrowly as a technology that expands access to in-classroom teaching can miss opportunities. Drawing on decades of lessons learned, we set out aims to help spur innovation in science education.


Open Learning at a Distance: Lessons for Struggling MOOCs
Patrick McAndrew, Eileen Scanlon

Science 20 December 2013:
Vol. 342 no. 6165 pp. 1450-1451
http://dx.doi.org/10.1126/science.1239686

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From funding agencies to scientific agency

The traditional peer review system for grant proposals is not always optimal. A new crowdfunding proposal based on advances in technology and mathematics could improve efficiency while retaining peer judgement.


From funding agencies to scientific agency
Collective allocation of science funding as an alternative to peer review
Johan Bollen, David Crandall, Damion Junk, Ying Ding, Katy Börner

EMBO reports
Early View

http://dx.doi.org/10.1002/embr.201338068

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Urban Mobility Scaling: Lessons from `Little Data'

Recent mobility scaling research, using new data sources, often relies on aggregated data alone. Hence, these studies face difficulties characterizing the influence of factors such as transportation mode on mobility patterns. This paper attempts to complement this research by looking at a category-rich mobility data set. In order to shed light on the impact of categories, as a case study, we use conventionally collected German mobility data. In contrast to `check-in'-based data, our results are not biased by Euclidean distance approximations. In our analysis, we show that aggregation can hide crucial differences between trip length distributions, when subdivided by categories. For example, we see that on an urban scale (0 to ~15 km), walking, versus driving, exhibits a highly different scaling exponent, thus universality class. Moreover, mode share and trip length are responsive to day-of-week and time-of-day. For example, in Germany, although driving is relatively less frequent on Sundays than on Wednesdays, trips seem to be longer. In addition, our work may shed new light on the debate between distance-based and intervening-opportunity mechanisms affecting mobility patterns, since mode may be chosen both according to trip length and urban form.


Urban Mobility Scaling: Lessons from `Little Data'
Galen Wilkerson, Ramin Khalili, Stefan Schmid

http://arxiv.org/abs/1401.0207

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The Metastable Brain

Neural ensembles oscillate across a broad range of frequencies and are transiently coupled or “bound” together when people attend to a stimulus, perceive, think, and act. This is a dynamic, self-assembling process, with parts of the brain engaging and disengaging in time. But how is it done? The theory of Coordination Dynamics proposes a mechanism called metastability, a subtle blend of integration and segregation. Tendencies for brain regions to express their individual autonomy and specialized functions (segregation, modularity) coexist with tendencies to couple and coordinate globally for multiple functions (integration). Although metastability has garnered increasing attention, it has yet to be demonstrated and treated within a fully spatiotemporal perspective. Here, we illustrate metastability in continuous neural and behavioral recordings, and we discuss theory and experiments at multiple scales, suggesting that metastable dynamics underlie the real-time coordination necessary for the brain’s dynamic cognitive, behavioral, and social functions.


The Metastable Brain

Emmanuelle Tognoli, J. A. Scott Kelso

Neuron, Volume 81, Issue 1, 35-48, 8 January 2014

http://dx.doi.org/10.1016/j.neuron.2013.12.022

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Beyond Big Data: Identifying Important Information for Real World Challenges

Beyond Big Data: Identifying Important Information for Real World Challenges | Papers | Scoop.it

Much of human inquiry today is focused on collecting massive quantities of data about complex systems, with the underlying assumption that more data leads to more insight into how to solve the challenges facing humanity. However, the questions we wish to address require identifying the impact of interventions on the behavior of a system, and to do this we must know which pieces of information are important and how they fit together. Here we describe why complex systems require different methods than simple systems and provide an overview of the corresponding paradigm shift in physics. We then connect the core ideas of the paradigm shift to information theory and describe how a parallel shift could take place in the study of complex biological and social systems. Finally, we provide a general framework for characterizing the importance of information. Framing scientific inquiry as an effort to objectively determine what is important and unimportant rather than collecting as much information as possible is a means for advancing our understanding and addressing many practical biological and social challenges.


Yaneer Bar-Yam and Maya Bialik, Beyond Big Data: Identifying important information for real world challenges

http://www.necsi.edu/projects/yaneer/information/

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Rebalancing the Global Economy

Rebalancing the Global Economy | Papers | Scoop.it

This special report includes 23 articles on topics ranging from technology, innovation and brand building to infrastructure, entrepreneurship and social impact. Current trends and recent developments shaping today’s global marketplace are covered, as are specific companies, industries and countries.
http://knowledge.wharton.upenn.edu/special-report/rebalancing-global-economy/

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‘Animals do think’ — surprising insights into the evolution of cognition and communication

Descartes thought all animals were machines — simple reflex devices that couldn't even think because they did not have language. About 200 years later, Darwin expressed a totally different view of animal behavior—that animals can think, albeit without language. And in the last 50 years, a new area in psychology emerged called animal cognition. That's not an oxymoron because — going back to Descartes — animals do, in fact, use thought to represent objects and events in their environments.


http://www.elsevier.com/connect/animals-do-think-surprising-insights-into-the-evolution-of-cognition-and-communication

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Human opinion dynamics: An inspiration to solve complex optimization problems

Human interactions give rise to the formation of different kinds of opinions in a society. The study of formations and dynamics of opinions has been one of the most important areas in social physics. The opinion dynamics and associated social structure leads to decision making or so called opinion consensus. Opinion formation is a process of collective intelligence evolving from the integrative tendencies of social influence with the disintegrative effects of individualisation, and therefore could be exploited for developing search strategies. Here, we demonstrate that human opinion dynamics can be utilised to solve complex mathematical optimization problems. The results have been compared with a standard algorithm inspired from bird flocking behaviour and the comparison proves the efficacy of the proposed approach in general. Our investigation may open new avenues towards understanding the collective decision making.


Human opinion dynamics: An inspiration to solve complex optimization problems
Rishemjit Kaur, Ritesh Kumar, Amol P. Bhondekar & Pawan Kapur

Scientific Reports 3, Article number: 3008 http://dx.doi.org/10.1038/srep03008


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António F Fonseca's curator insight, December 28, 2013 7:14 AM

Another paper on opinion dynamics.

Luciano Lampi's curator insight, January 11, 2014 5:45 PM

Humanrithms....

Claude Emond's curator insight, January 20, 2014 5:51 PM

Opinions are an unescapable part of sharing and influencing the direction of collective intelligence

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Epidemics on social networks

Since its first formulations almost a century ago, mathematical models for disease spreading contributed to understand, evaluate and control the epidemic processes.They promoted a dramatic change in how epidemiologists thought of the propagation of infectious diseases.In the last decade, when the traditional epidemiological models seemed to be exhausted, new types of models were developed.These new models incorporated concepts from graph theory to describe and model the underlying social structure.Many of these works merely produced a more detailed extension of the previous results, but some others triggered a completely new paradigm in the mathematical study of epidemic processes. In this review, we will introduce the basic concepts of epidemiology, epidemic modeling and networks, to finally provide a brief description of the most relevant results in the field.


Epidemics on social networks
Marcelo N. Kuperman

http://arxiv.org/abs/1312.3838

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António F Fonseca's curator insight, January 9, 2014 5:10 AM

A good review about epidemic models in social networks, SIS, SIR, etc ...

Marco Valli's curator insight, January 9, 2014 9:08 AM

Basics of SIS/SIR models of spreading epidemics, and their relations to social networks.

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Nonlocal and global dynamics of cellular automata: A theoretical computer arithmetic for real maps

A fully-discrete general method to approximate any real map in the unit interval by a cellular automaton (CA) to arbitrary precision is presented. This result leads to establish a one-to-one correspondence between the qualitative behavior found in bifurcation diagrams of real nonlinear maps and the Wolfram classes of CAs. The local, nonlocal and global dynamical behaviors of CAs are systematically addressed and universal maps are derived for the three levels of description showing their direct interrelationships and elucidating some essential aspects of their dynamics. None of the maps contain any freely adjustable parameter and they are valid for any number of symbols in the alphabet p and neighborhood range ρ. The method is applied to the logistic map, for which a logistic CA is derived. All dynamical behavior present in the former is shown to be exactly reproduced by the latter.


Nonlocal and global dynamics of cellular automata: A theoretical computer arithmetic for real maps
Vladimir Garcia-Morales

http://arxiv.org/abs/1312.6534

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Special issue: What is reality? - New Scientist

Special issue: What is reality? - New Scientist | Papers | Scoop.it
The more we learn about reality, the less we understand it. Our special collection of articles explores how we define reality, what it could be and whether it exists

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FastTFriend's curator insight, December 21, 2013 5:39 AM

 But what is reality? The more we probe it, the harder it becomes to comprehend. In the eight articles on this page we take a tour of our fundamental understanding of the world around us, starting with an attempt to define reality and ending with the idea that whatever reality is, it isn’t what it seems.

Luciano Lampi's curator insight, January 8, 2014 11:55 AM

Dream about this question....

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How Can the Study of Complexity Transform Our Understanding of the World?

How Can the Study of Complexity Transform Our Understanding of the World? | Papers | Scoop.it

The “study of complexity” refers to the attempt to find common principles underlying the behavior of complex systems—systems in which large collections of components interact in nonlinear ways. Here, the term nonlinear implies that the system can’t be understood simply by understanding its individual components; nonlinear interactions cause the whole to be “more than the sum of its parts.”


How Can the Study of Complexity Transform Our Understanding of the World?

Melanie Mitchell

https://www.bigquestionsonline.com/content/how-can-study-complexity-transform-our-understanding-world

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António F Fonseca's curator insight, January 22, 2014 4:45 AM

Wonderful and clarifying text.

Lorien Pratt's curator insight, January 22, 2014 11:20 PM

One of my favorite complexity authors.  An excerpt: "In the past it was widely assumed that such phenomena are hard to predict because the underlying processes are highly complex, and that random factors must play a key role.  However, Complex Systems science—especially the study of dynamics and chaos—have shown that complex behavior and unpredictability can arise in a system even if the underlying rules are extremely simple and completely deterministic.  Often, the key to complexity is the iteration over time of simple, though nonlinear, interaction rules among the system’s components."


This insight is at the core of Decision Intelligence, which adds an understanding of these emergent behaviors to the usual big data/predictive analytics/optimization stack.

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Haunted by His Brother, He Revolutionized Physics

Haunted by His Brother, He Revolutionized Physics | Papers | Scoop.it

Time. As a physicist, Wheeler had always been curious to untangle the nature of that mysterious dimension. But now, in the wake of Joe’s death, it was personal.
Wheeler would spend the rest of his life struggling against time. His journals, which he always kept at hand (and which today are stashed, unpublished, in the archives of the American Philosophical Society Library in Philadelphia), reveal a stunning portrait of an obsessed thinker, ever-aware of his looming mortality, caught in a race against time to answer not a question, but the question: “How come existence?”
“Of all obstacles to a thoroughly penetrating account of existence, none looms up more dismayingly than ‘time,’” Wheeler wrote. “Explain time? Not without explaining existence. Explain existence? Not without explaining time.”

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Multi-scale community organization of the human structural connectome and its relationship with resting-state functional connectivity

The human connectome has been widely studied over the past decade. A principal finding is that it can be decomposed into communities of densely interconnected brain regions. Past studies have often used single-scale modularity measures in order to infer the connectome's community structure, possibly overlooking interesting structure at other organizational scales. In this report, we used the partition stability framework, which defines communities in terms of a Markov process (random walk), to infer the connectome's multi-scale community structure. Comparing the community structure to observed resting-state functional connectivity revealed communities across a broad range of scales that were closely related to functional connectivity. This result suggests a mapping between communities in structural networks, models of influence-spreading and diffusion, and brain function. It further suggests that the spread of influence among brain regions may not be limited to a single characteristic scale.


Multi-scale community organization of the human structural connectome and its relationship with resting-state functional connectivity
RICHARD F. BETZEL, ALESSANDRA GRIFFA, ANDREA AVENA-KOENIGSBERGER, JOAQUÍN GOÑI, JEAN-PHILIPPE THIRAN, PATRIC HAGMANN, OLAF SPORNS
Network Science , Volume 1 , Issue 03 , December 2013, pp 353 - 373
http://dx.doi.org/10.1017/nws.2013.19

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On the biological and cultural evolution of shame: Using internet search tools to weight values in many cultures

Shame has clear biological roots and its precise form of expression affects social cohesion and cultural characteristics. Here we explore the relative importance between shame and guilt by using Google Translate to produce translation for the words shame, guilt, pain, embarrassment and fear to the 64 languages covered. We also explore the meanings of these concepts among the Yanomami, a horticulturist hunter-gatherer tribe in the Orinoquia. Results show that societies previously described as 'guilt societies' have more words for guilt than for shame, but the large majority, including the societies previously described as 'shame societies', have more words for shame than for guilt. Results are consistent with evolutionary models of shame which predict a wide scatter in the relative importance between guilt and shame, suggesting that cultural evolution of shame has continued the work of biological evolution, and that neither provides a strong adaptive advantage to either shame or guilt. We propose that the study of shame will improve our understanding of the interaction between biological and cultural evolution in the evolution of cognition and emotions.


On the biological and cultural evolution of shame: Using internet search tools to weight values in many cultures
Klaus Jaffe, Astrid Florez, Cristina M Gomes, Daniel Rodriguez, Carla Achury

http://arxiv.org/abs/1401.1100

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A Creepy World

Using the mechanics of creep in material sciences as a metaphor, we present a general framework to understand the evolution of financial, economic and social systems and to construct scenarios for the future. In a nutshell, highly non-linear out-of-equilibrium systems subjected to exogenous perturbations tend to exhibit a long phase of slow apparent stable evolution, which are nothing but slow maturations towards instabilities, failures and changes of regimes. With examples from history where a small event had a cataclysmic consequence, we propose a novel view of the current state of the world via the logical scenarios that derive, avoiding the traps of an illusionary stability and simple linear extrapolation. The endogenous scenarios are "muddling along", "managing through" and "blood red abyss". The exogenous scenarios are "painful adjustment" and "golden east".


A Creepy World
Didier Sornette, Peter Cauwels

http://arxiv.org/abs/1401.3281

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Embodied social interaction constitutes social cognition in pairs of humans: A minimalist virtual reality experiment

Embodied social interaction constitutes social cognition in pairs of humans: A minimalist virtual reality experiment | Papers | Scoop.it

Scientists have traditionally limited the mechanisms of social cognition to one brain, but recent approaches claim that interaction also realizes cognitive work. Experiments under constrained virtual settings revealed that interaction dynamics implicitly guide social cognition. Here we show that embodied social interaction can be constitutive of agency detection and of experiencing another's presence. Pairs of participants moved their “avatars” along an invisible virtual line and could make haptic contact with three identical objects, two of which embodied the other's motions, but only one, the other's avatar, also embodied the other's contact sensor and thereby enabled responsive interaction. Co-regulated interactions were significantly correlated with identifications of the other's avatar and reports of the clearest awareness of the other's presence. These results challenge folk psychological notions about the boundaries of mind, but make sense from evolutionary and developmental perspectives: an extendible mind can offload cognitive work into its environment.


Embodied social interaction constitutes social cognition in pairs of humans: A minimalist virtual reality experiment
Tom Froese, Hiroyuki Iizuka & Takashi Ikegami

Scientific Reports 4, Article number: 3672 http://dx.doi.org/10.1038/srep03672

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António F Fonseca's curator insight, January 17, 2014 3:57 AM

More experiments with our social brain.

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Goodbye Copernicus, Hello Universe

Goodbye Copernicus, Hello Universe | Papers | Scoop.it

When Copernicus told us more than 400 years ago that the Earth was not at the center of the universe, he could hardly have imagined that it would lead this far. At the hands of astronomy and cosmology, we seem to have been reduced to near nothingness, specks within slivers of time and space, inside specks that are themselves entire universes. But how should we interpret this fact? Does this ultimate extension of the Copernican narrative seal our infinitely mediocre fate? The question is more complex than it initially seems.

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Scale-free power-laws as interaction between progress and diffusion

While scale-free power-laws are frequently found in social and technological systems, their authenticity, origin, and gained insights are often questioned, and rightfully so. The article presents a newly found rank-frequency power-law that aligns the top-500 supercomputers according to their performance. Pursuing a cautious approach in a systematic way, we check for authenticity, evaluate several potential generative mechanisms, and ask the “so what” question. We evaluate and finally reject the applicability of well-known potential generative mechanisms such as preferential attachment, self-organized criticality, optimization, and random observation. Instead, the microdata suggest that an inverse relationship between exponential technological progress and exponential technology diffusion through social networks results in the identified fat-tail distribution. This newly identified generative mechanism suggests that the supply and demand of technology (“technology push” and “demand pull”) align in exponential synchronicity, providing predictive insights into the evolution of highly uncertain technology markets.


Scale-free power-laws as interaction between progress and diffusion
Martin Hilbert

Complexity
Early View

http://dx.doi.org/10.1002/cplx.21485

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Structural balance in the social networks of a wild mammal

•We tested the theory of structural balance (i.e. ‘the enemy of my enemy is my friend’) in rock hyrax social networks.
•We found that in accordance with structural balance, hyraxes tend to form balanced triads.
•Hyraxes changed their social configurations over time, moving into more balanced triads.
•New individuals in the population introduced social instability.
•Triad sex ratio affected the triad type it changed to.


Structural balance in the social networks of a wild mammal
Amiyaal Ilany, Adi Barocas, Lee Koren, Michael Kam, Eli Geffen

Animal Behaviour
Volume 85, Issue 6, June 2013, Pages 1397–1405

http://dx.doi.org/10.1016/j.anbehav.2013.03.032

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A Scalable Heuristic for Viral Marketing Under the Tipping Model

In a "tipping" model, each node in a social network, representing an individual, adopts a property or behavior if a certain number of his incoming neighbors currently exhibit the same. In viral marketing, a key problem is to select an initial "seed" set from the network such that the entire network adopts any behavior given to the seed. Here we introduce a method for quickly finding seed sets that scales to very large networks. Our approach finds a set of nodes that guarantees spreading to the entire network under the tipping model. After experimentally evaluating 31 real-world networks, we found that our approach often finds seed sets that are several orders of magnitude smaller than the population size and outperform nodal centrality measures in most cases. In addition, our approach scales well - on a Friendster social network consisting of 5.6 million nodes and 28 million edges we found a seed set in under 3.6 hours. Our experiments also indicate that our algorithm provides small seed sets even if high-degree nodes are removed. Lastly, we find that highly clustered local neighborhoods, together with dense network-wide community structures, suppress a trend's ability to spread under the tipping model.


A Scalable Heuristic for Viral Marketing Under the Tipping Model
Paulo Shakarian, Sean Eyre, Damon Paulo

http://arxiv.org/abs/1309.2963

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The expert game -- Cooperation in social communication

Large parts of professional human communication proceed in a request-reply fashion, whereby requests contain specifics of the information desired while replies can deliver the required information. However, time limitations often force individuals to prioritize some while neglecting others. This dilemma will inevitably force individuals into defecting against some communication partners to give attention to others. Furthermore, communication entirely breaks down when individuals act purely egoistically as replies would never be issued and quest for desired information would always be prioritized. Here we present an experiment, termed "The expert game", where a number of individuals communicate with one-another through an electronic messaging system. By imposing a strict limit on the number of sent messages, individuals were required to decide between requesting information that is beneficial for themselves or helping others by replying to their requests. In the experiment, individuals were assigned the task to find the expert on a specific topic and receive a reply from that expert. Tasks and expertise of each player were periodically re-assigned to randomize the required interactions. Resisting this randomization, a non-random network of cooperative communication between individuals formed. We use a simple Bayesian inference algorithm to model each player's trust in the cooperativity of others with good experimental agreement. Our results suggest that human communication in groups of individuals is strategic and favors cooperation with trusted parties at the cost of defection against others. To establish and maintain trusted links a significant fraction of time-resources is allocated, even in situations where the information transmitted is negligible.


The expert game -- Cooperation in social communication
Kristian Moss Bendtsen, Florian Uekermann, Jan O. Haerter

http://arxiv.org/abs/1312.6715

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Persistence of social signatures in human communication

We combine cell phone data with survey responses to show that a person’s social signature, as we call the pattern of their interactions with different friends and family members, is remarkably robust. People focus a high proportion of their communication efforts on a small number of individuals, and this behavior persists even when there are changes in the identity of the individuals involved. Although social signatures vary between individuals, a given individual appears to retain a specific social signature over time. Our results are likely to reflect limitations in the ability of humans to maintain many emotionally close relationships, both because of limited time and because the emotional “capital” that individuals can allocate between family members and friends is finite.


Persistence of social signatures in human communication

Jari Saramäki, E. A. Leicht, Eduardo López, Sam G. B. Roberts, Felix Reed-Tsochas, and Robin I. M. Dunbar

PNAS

http://dx.doi.org/10.1073/pnas.1308540110

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