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Topical issue: Temporal Network Theory and Applications Eur. Phys. J. B 

The power of any kind of network approach lies in the ability to simplify a complex system so that one can better understand its function as a whole. Sometimes it is beneficial, however, to include more information than in a simple graph of only nodes and links. Adding information about times of interactions can make predictions and mechanistic understanding more accurate. The drawback, however, is that there are not so many methods available, partly because temporal networks is a relatively young field, partly because it is more difficult to develop such methods compared to for static networks. In this colloquium, we review the methods to analyze and model temporal networks and processes taking place on them, focusing mainly on the last three years. This includes the spreading of infectious disease, opinions, rumors, in social networks; information packets in computer networks; various types of signaling in biology, and more. We also discuss future directions.

 

Modern temporal network theory: a colloquium*
Petter Holme

Topical issue: Temporal Network Theory and Applications
Eur. Phys. J. B (2015) 88: 234
http://dx.doi.org/10.1140/epjb/e2015-60657-4

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See Topical Issue: http://epjb.epj.org/component/toc/?task=topic&id=492

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Linking Individual and Collective Behavior in Adaptive Social Networks

Adaptive social structures are known to promote the evolution of cooperation. However, up to now the characterization of the collective, population-wide dynamics resulting from the self-organization of individual strategies on a coevolving, adaptive network has remained unfeasible. Here we establish a (reversible) link between individual (micro)behavior and collective (macro)behavior for coevolutionary processes. We demonstrate that an adaptive network transforms a two-person social dilemma locally faced by individuals into a collective dynamics that resembles that associated with an N-person coordination game, whose characterization depends sensitively on the relative time scales between the entangled behavioral and network evolutions. In particular, we show that the faster the relative rate of adaptation of the network, the smaller the critical fraction of cooperators required for cooperation to prevail, thus establishing a direct link between network adaptation and the evolution of cooperation. The framework developed here is general and may be readily applied to other dynamical processes occurring on adaptive networks, notably, the spreading of contagious diseases or the diffusion of innovations.

 

Linking Individual and Collective Behavior in Adaptive Social Networks
Flávio L. Pinheiro, Francisco C. Santos, and Jorge M. Pacheco
Phys. Rev. Lett. 116, 128702

http://dx.doi.org/10.1103/PhysRevLett.116.128702

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If networks adapt faster, then less cooperators are required for cooperation to prevail.

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Exploring the quantum speed limit with computer games

Exploring the quantum speed limit with computer games | Papers | Scoop.it

Humans routinely solve problems of immense computational complexity by intuitively forming simple, low-dimensional heuristic strategies1, 2. Citizen science (or crowd sourcing) is a way of exploiting this ability by presenting scientific research problems to non-experts. ‘Gamification’—the application of game elements in a non-game context—is . an effective tool with which to enable citizen scientists to provide solutions to research problems. The citizen science games Foldit3, EteRNA4 and EyeWire5 have been used successfully to study protein and RNA folding and neuron mapping, but so far gamification has not been applied to problems in quantum physics. Here . we report on Quantum Moves, an online platform gamifying optimization problems in quantum physics. We show that human players are able to find solutions to difficult problems associated with the task of quantum computing6. Players succeed where purely numerical optimization fails, and analyses of their solutions provide insights into the problem of optimization of a more profound and general nature. Using player strategies, we have thus developed a few-parameter heuristic optimization method that efficiently outperforms the most prominent established numerical methods. The numerical complexity associated with time-optimal solutions increases for shorter process durations. To understand this better, we produced a low-dimensional rendering of the optimization landscape. This rendering reveals why traditional optimization methods fail near the quantum speed limit (that is, the shortest process duration with perfect fidelity)7, 8, 9. Combined analyses of optimization landscapes and heuristic solution strategies may benefit wider classes of optimization problems in quantum physics and beyond.

 

Exploring the quantum speed limit with computer games
• Jens Jakob W. H. Sørensen, Mads Kock Pedersen, Michael Munch, Pinja Haikka, Jesper Halkjær Jensen, Tilo Planke, Morten Ginnerup Andreasen, Miroslav Gajdacz, Klaus Mølmer, Andreas Lieberoth & Jacob F. Sherson

Nature 532, 210–213 (14 April 2016) http://dx.doi.org/10.1038/nature17620

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A Possible Link Between Pyriproxyfen and Microcephaly

The Zika virus is the primary suspect in the large increase in microcephaly cases in 2015-6 in Brazil, however its role is unconfirmed despite individual cases of viral infections found in neural tissue. Here we consider the alternative that the insecticide pyriproxyfen, used in Brazilian drinking water for mosquito control, may actually be the cause. Pyriproxifen is an analog of juvenile hormone, which corresponds in mammals to regulatory molecules including retinoic acid, a vitamin A metabolite, with which it has cross-reactivity and whose application during development causes microcephaly. Methoprene, another juvenile hormone analog approved as an insecticide has metabolites that bind to the retinoid X receptor, and causes developmental disorders in mammals. Isotretinoin is another example of a retinoid causing microcephaly in human babies via activation of the retinoid X receptor. Moreover, tests of pyriproxyfen by the manufacturer, Sumitomo, widely quoted as giving no evidence for developmental toxicity, actually found some evidence for such an effect, including low brain mass and arhinencephaly--incomplete formation of the anterior cerebral hemispheres--in rat pups. Finally, the pyriproxyfen use in Brazil is unprecedented--it has never before been applied to a water supply on such a scale. Claims that it is not being used in Recife, the epicenter of microcephaly cases, do not distinguish the metropolitan area of Recife, where it is widely used, and the municipality, where it is not. Given this combination of information we strongly recommend that the use of pyriproxyfen in Brazil be suspended pending further investigation.

 

A Possible Link Between Pyriproxyfen and Microcephaly
Dan Evans, Fred Nijhout, Raphael Parens, Alfredo J. Morales, Yaneer Bar-Yam

http://arxiv.org/abs/1604.03834

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Calling Dunbar's Numbers

The social brain hypothesis predicts that humans have an average of about 150 relationships at any given time. Within this 150, there are layers of friends of an ego, where the number of friends in a layer increases as the emotional closeness decreases. Here we analyse a mobile phone dataset, firstly, to ascertain whether layers of friends can be identified based on call frequency. We then apply different clustering algorithms to break the call frequency of egos into clusters and compare the number of alters in each cluster with the layer size predicted by the social brain hypothesis. In this dataset we find strong evidence for the existence of a layered structure. The clustering yields results that match well with previous studies for the innermost and outermost layers, but for layers in between we observe large variability.

 

Calling Dunbar's Numbers
Pádraig MacCarron, Kimmo Kaski, Robin Dunbar

http://arxiv.org/abs/1604.02400

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Users Polarization on Facebook and Youtube

On social media algorithms for content promotion, accounting for users preferences, might limit the exposure to unsolicited contents. In this work, we study how the same contents (videos) are consumed on different platforms -- i.e. Facebook and YouTube -- over a sample of 12M of users. Our findings show that the same content lead to the formation of echo chambers, irrespective of the online social network and thus of the algorithm for content promotion. Finally, we show that the users' commenting patterns are accurate early predictors for the formation of echo-chambers.

 

Users Polarization on Facebook and Youtube
Alessandro Bessi, Fabiana Zollo, Michela Del Vicario, Michelangelo Puliga, Antonio Scala, Guido Caldarelli, Brian Uzzi, Walter Quattrociocchi

http://arxiv.org/abs/1604.02705

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Discovering governing equations from data by sparse identification of nonlinear dynamical systems

Understanding dynamic constraints and balances in nature has facilitated rapid development of knowledge and enabled technology, including aircraft, combustion engines, satellites, and electrical power. This work develops a novel framework to discover governing equations underlying a dynamical system simply from data measurements, leveraging advances in sparsity techniques and machine learning. The resulting models are parsimonious, balancing model complexity with descriptive ability while avoiding overfitting. There are many critical data-driven problems, such as understanding cognition from neural recordings, inferring climate patterns, determining stability of financial markets, predicting and suppressing the spread of disease, and controlling turbulence for greener transportation and energy. With abundant data and elusive laws, data-driven discovery of dynamics will continue to play an important role in these efforts.

 

Discovering governing equations from data by sparse identification of nonlinear dynamical systems
Steven L. Brunton, Joshua L. Proctor, and J. Nathan Kutz

PNAS

http://dx.doi.org/ 10.1073/pnas.1517384113

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Why the National Institutes of Health Should Replace Peer Review With a Lottery

Why the National Institutes of Health Should Replace Peer Review With a Lottery | Papers | Scoop.it

A major advantage of using a funding lottery would be that, by reducing its reliance on peer-review rankings, the NIH would have more room to address the urgent problem of bias. A suitably designed lottery system could help eliminate the small but persistent gender gap, and the larger racial gap in the funding it awards, by giving NIH officers more leeway to include a representative set of proposals. And importantly, a lottery would be an honest acknowledgement of what most scientists already sense: that, despite its reputation for basing decisions on merit, peer review is a much more random process than we would like to admit.

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Durably reducing transphobia: A field experiment on door-to-door canvassing

Existing research depicts intergroup prejudices as deeply ingrained, requiring intense intervention to lastingly reduce. Here, we show that a single approximately 10-minute conversation encouraging actively taking the perspective of others can markedly reduce prejudice for at least 3 months. We illustrate this potential with a door-to-door canvassing intervention in South Florida targeting antitransgender prejudice. Despite declines in homophobia, transphobia remains pervasive. For the intervention, 56 canvassers went door to door encouraging active perspective-taking with 501 voters at voters’ doorsteps. A randomized trial found that these conversations substantially reduced transphobia, with decreases greater than Americans’ average decrease in homophobia from 1998 to 2012. These effects persisted for 3 months, and both transgender and nontransgender canvassers were effective. The intervention also increased support for a nondiscrimination law, even after exposing voters to counterarguments.

 

Durably reducing transphobia: A field experiment on door-to-door canvassing
David Broockman, Joshua Kalla

Science  08 Apr 2016:
Vol. 352, Issue 6282, pp. 220-224
http://dx.doi.org/10.1126/science.aad9713

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Understanding the group dynamics and success of teams

Complex problems often require coordinated group effort and can consume significant resources, yet our understanding of how teams form and succeed has been limited by a lack of large-scale, quantitative data. We analyse activity traces and success levels for approximately 150 000 self-organized, online team projects. While larger teams tend to be more successful, workload is highly focused across the team, with only a few members performing most work. We find that highly successful teams are significantly more focused than average teams of the same size, that their members have worked on more diverse sets of projects, and the members of highly successful teams are more likely to be core members or ‘leads’ of other teams. The relations between team success and size, focus and especially team experience cannot be explained by confounding factors such as team age, external contributions from non-team members, nor by group mechanisms such as social loafing. Taken together, these features point to organizational principles that may maximize the success of collaborative endeavours.

 

Understanding the group dynamics and success of teams
Michael Klug, James P. Bagrow

Royal Society Open Science

http://dx.doi.org/10.1098/rsos.160007

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Multilayer Stochastic Block Models Reveal the Multilayer Structure of Complex Networks

Multilayer Stochastic Block Models Reveal the Multilayer Structure of Complex Networks | Papers | Scoop.it

In complex systems, the network of interactions we observe between systems components is the aggregate of the interactions that occur through different mechanisms or layers. Recent studies reveal that the existence of multiple interaction layers can have a dramatic impact in the dynamical processes occurring on these systems. However, these studies assume that the interactions between systems components in each one of the layers are known, while typically for real-world systems we do not have that information. Here, we address the issue of uncovering the different interaction layers from aggregate data by introducing multilayer stochastic block models (SBMs), a generalization of single-layer SBMs that considers different mechanisms of layer aggregation. First, we find the complete probabilistic solution to the problem of finding the optimal multilayer SBM for a given aggregate-observed network. Because this solution is computationally intractable, we propose an approximation that enables us to verify that multilayer SBMs are more predictive of network structure in real-world complex systems.

 

Multilayer Stochastic Block Models Reveal the Multilayer Structure of Complex Networks
Toni Vallès-Català, Francesco A. Massucci, Roger Guimerà, and Marta Sales-Pardo
Phys. Rev. X 6, 011036 – Published 31 March 2016

http://dx.doi.org/10.1103/PhysRevX.6.011036

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Self-regulatory information sharing in participatory social sensing

Participation in social sensing applications is challenged by privacy threats. Large-scale access to citizens’ data allow surveillance and discriminatory actions that may result in segregation phenomena in society. On the contrary are the benefits of accurate computing analytics required for more informed decision-making, more effective policies and regulation of techno-socio-economic systems supported by ‘Internet-of Things’ technologies. In contrast to earlier work that either focuses on privacy protection or Big Data analytics, this paper proposes a self-regulatory information sharing system that bridges this gap. This is achieved by modeling information sharing as a supply-demand system run by computational markets. On the supply side lie the citizens that make incentivized but self-determined decisions about the level of information they share. On the demand side stand data aggregators that provide rewards to citizens to receive the required data for accurate analytics. The system is empirically evaluated with two real-world datasets from two application domains: (i) Smart Grids and (ii) mobile phone sensing. Experimental results quantify trade-offs between privacy-preservation, accuracy of analytics and costs from the provided rewards under different experimental settings. Findings show a higher privacy-preservation that depends on the number of participating citizens and the type of data summarized. Moreover, analytics with summarization data tolerate high local errors without a significant influence on the global accuracy. In other words, local errors cancel out. Rewards can be optimized to be fair so that citizens with more significant sharing of information receive higher rewards. All these findings motivate a new paradigm of truly decentralized and ethical data analytics.

 

Self-regulatory information sharing in participatory social sensing
Evangelos Pournaras, Jovan Nikolic, Pablo Velásquez, Marcello Trovati, Nik Bessis and Dirk Helbing
EPJ Data Science 2016 5:14
http://dx.doi.org/10.1140/epjds/s13688-016-0074-4

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The dynamics of information-driven coordination phenomena: A transfer entropy analysis

Data from social media provide unprecedented opportunities to investigate the processes that govern the dynamics of collective social phenomena. We consider an information theoretical approach to define and measure the temporal and structural signatures typical of collective social events as they arise and gain prominence. We use the symbolic transfer entropy analysis of microblogging time series to extract directed networks of influence among geolocalized subunits in social systems. This methodology captures the emergence of system-level dynamics close to the onset of socially relevant collective phenomena. The framework is validated against a detailed empirical analysis of five case studies. In particular, we identify a change in the characteristic time scale of the information transfer that flags the onset of information-driven collective phenomena. Furthermore, our approach identifies an order-disorder transition in the directed network of influence between social subunits. In the absence of clear exogenous driving, social collective phenomena can be represented as endogenously driven structural transitions of the information transfer network. This study provides results that can help define models and predictive algorithms for the analysis of societal events based on open source data.

 

The dynamics of information-driven coordination phenomena: A transfer entropy analysis
Javier Borge-Holthoefer, Nicola Perra, Bruno Gonçalves, Sandra González-Bailón, Alex Arenas, Yamir Moreno, and Alessandro Vespignani

Science Advances  01 Apr 2016:
Vol. 2, no. 4, e1501158
http://dx.doi.org/10.1126/sciadv.1501158

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The physics of multilayer networks

The study of networks plays a crucial role in investigating the structure, dynamics, and function of a wide variety of complex systems in myriad disciplines. Despite the success of traditional network analysis, standard networks provide a limited representation of these systems, which often includes different types of relationships (i.e., "multiplexity") among their constituent components and/or multiple interacting subsystems. Such structural complexity has a significant effect on both dynamics and function. Throwing away or aggregating available structural information can generate misleading results and provide a major obstacle towards attempts to understand the system under analysis. The recent "multilayer' approach for modeling networked systems explicitly allows the incorporation of multiplexity and other features of realistic networked systems. On one hand, it allows one to couple different structural relationships by encoding them in a convenient mathematical object. On the other hand, it also allows one to couple different dynamical processes on top of such interconnected structures. The resulting framework plays a crucial role in helping to achieve a thorough, accurate understanding of complex systems. The study of multilayer networks has also revealed new physical phenomena that remained hidden when using the traditional network representation of graphs. Here we survey progress towards a deeper understanding of dynamical processes on multilayer networks, and we highlight some of the physical phenomena that emerge from multilayer structure and dynamics.

 

The physics of multilayer networks
Manlio De Domenico, Clara Granell, Mason A. Porter, Alex Arenas

http://arxiv.org/abs/1604.02021#

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From Big Data To Important Information

Advances in science are being sought in newly available opportunities to collect massive quantities of data about complex systems. While key advances are being made in detailed mapping of systems, how to relate this data to solving many of the challenges facing humanity is unclear. The questions we often wish to address require identifying the impact of interventions on the system and that impact is not apparent in the detailed data that is available. Here we review key concepts and motivate a general framework for building larger scale views of complex systems and for characterizing the importance of information in physical, biological and social systems. We provide examples of its application to evolutionary biology with relevance to ecology, biodiversity, pandemics, and human lifespan, and in the context of social systems with relevance to ethnic violence, global food prices, and stock market panic. Framing scientific inquiry as an effort to determine what is important and unimportant is a means for advancing our understanding and addressing many practical concerns, such as economic development or treating disease.

 

From Big Data To Important Information
Yaneer Bar-Yam

http://arxiv.org/abs/1604.00976

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Time Slices: What Is the Duration of a Percept?

We experience the world as a seamless stream of percepts. However, intriguing illusions and recent experiments suggest that the world is not continuously translated into conscious perception. Instead, perception seems to operate in a discrete manner, just like movies appear continuous although they consist of discrete images. To explain how the temporal resolution of human vision can be fast compared to sluggish conscious perception, we propose a novel conceptual framework in which features of objects, such as their color, are quasi-continuously and unconsciously analyzed with high temporal resolution. Like other features, temporal features, such as duration, are coded as quantitative labels. When unconscious processing is “completed,” all features are simultaneously rendered conscious at discrete moments in time, sometimes even hundreds of milliseconds after stimuli were presented.

 

Time Slices: What Is the Duration of a Percept?
Michael H. Herzog, Thomas Kammer,  Frank Scharnowski

PLoS Biol 14(4): e1002433. http://dx.doi.org/10.1371/journal.pbio.1002433 

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Detection of timescales in evolving complex systems

Most complex systems are intrinsically dynamic in nature. The evolution of a dynamic complex system is typically represented as a sequence of snapshots, where each snapshot describes the configuration of the system at a particular instant of time. Then, one may directly follow how the snapshots evolve in time, or aggregate the snapshots within some time intervals to form representative "slices" of the evolution of the system configuration. This is often done with constant intervals, whose duration is based on arguments on the nature of the system and of its dynamics. A more refined approach would be to consider the rate of activity in the system to perform a separation of timescales. However, an even better alternative would be to define dynamic intervals that match the evolution of the system's configuration. To this end, we propose a method that aims at detecting evolutionary changes in the configuration of a complex system, and generates intervals accordingly. We show that evolutionary timescales can be identified by looking for peaks in the similarity between the sets of events on consecutive time intervals of data. Tests on simple toy models reveal that the technique is able to detect evolutionary timescales of time-varying data both when the evolution is smooth as well as when it changes sharply. This is further corroborated by analyses of several real datasets. Our method is scalable to extremely large datasets and is computationally efficient. This allows a quick, parameter-free detection of multiple timescales in the evolution of a complex system.

Detection of timescales in evolving complex systems
Richard K. Darst, Clara Granell, Alex Arenas, Sergio Gómez, Jari Saramäki, Santo Fortunato

http://arxiv.org/abs/1604.00758

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A global take on congestion in urban areas

We analyze the congestion data collected by a GPS device company (TomTom) for almost 300 urban areas in the world. Using simple scaling arguments and data fitting we show that congestion during peak hours in large cities grows essentially as the square root of the population density. This result, at odds with previous publications showing that gasoline consumption decreases with density, confirms that density is indeed an important determinant of congestion, but also that we need urgently a better theoretical understanding of this phenomena. This incomplete view at the urban level leads thus to the idea that thinking about density by itself could be very misleading in congestion studies, and that it is probably more useful to focus on the spatial redistribution of activities and residences.

 

A global take on congestion in urban areas
Marc Barthelemy

http://arxiv.org/abs/1604.03904

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Predation risk drives social complexity in cooperative breeders

It is widely accepted that high predation risk may select for group living, but predation is not regarded as a primary driver of social complexity. This view neglects the important effect of predation on dispersal and offspring survival, which may require cooperation among group members. The significance of predation for the evolution of social complexity can be well illustrated by behavioral and morphological adaptations of highly social animals showing division of labor, such as eusocial insects and cooperatively breeding fishes. By examining the diversity of social organization in a cooperative cichlid in relation to ecological variation, we show that predation risk has the greatest explanatory power of social complexity. This stresses the significance of predation for social evolution.

Via Samir
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Hybrid Societies: Challenges and Perspectives in the Design of Collective Behavior in Self-organizing Systems

Hybrid societies are self-organizing, collective systems, which are composed of different components, for example, natural and artificial parts (bio-hybrid) or human beings interacting with and through technical systems (socio-technical). Many different disciplines investigate methods and systems closely related to the design of hybrid societies. A stronger collaboration between these disciplines could allow for re-use of methods and create significant synergies. We identify three main areas of challenges in the design of self-organizing hybrid societies. First, we identify the formalization challenge. There is an urgent need for a generic model that allows a description and comparison of collective hybrid societies. Second, we identify the system design challenge. Starting from the formal specification of the system, we need to develop an integrated design process. Third, we identify the challenge of interdisciplinarity. Current research on self-organizing hybrid societies stretches over many different fields and hence requires the re-use and synthesis of methods at intersections between disciplines. We then conclude by presenting our perspective for future approaches with high potential in this area.

 

Hybrid Societies: Challenges and Perspectives in the Design of Collective Behavior in Self-organizing Systems

Heiko Hamann, Yara Khaluf, Jean Botev, Mohammad Divband Soorati, Eliseo Ferrante, Oliver Kosak, Jean-Marc Montanier, Sanaz Mostaghim, Richard Redpath, Jonathan Timmis, Frank Veenstra, Mostafa Wahby, Aleš Zamuda
Front. Robot. AI, 11 April 2016 | http://dx.doi.org/10.3389/frobt.2016.00014

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Why Nature Prefers Hexagons

Why Nature Prefers Hexagons | Papers | Scoop.it

How do bees do it? The honeycombs in which they store their amber nectar are marvels of precision engineering, an array of prism-shaped cells with a perfectly hexagonal cross-section. The wax walls are made with a very precise thickness, the cells are gently tilted from the horizontal to prevent the viscous honey from running out, and the entire comb is aligned with the Earth’s magnetic field. Yet this structure is made without any blueprint or foresight, by many bees working simultaneously and somehow coordinating their efforts to avoid mismatched cells.

 

http://nautil.us/issue/35/boundaries/why-nature-prefers-hexagons

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What the Panama Papers Mean for Transparency and ‘Dark Money’

What the Panama Papers Mean for Transparency and ‘Dark Money’ | Papers | Scoop.it

Last Sunday, the Washington, D.C.-based International Consortium of Investigative Journalists (ICIJ) published a massive leak of some 11.5 million documents covering nearly four decades that showed how world leaders, politicians and businesses hide and launder their money, evade taxes and finance arms and drug deals. The source of the leak is a little-known but powerful law firm in Panama called Mossack Fonseca, which the ICIJ describes as one of the top creators of shell companies and corporate structures that can be used to hide ownership of assets.

 

The “Panama Papers,” as the leaked documents are called, offer a rare opportunity to regulators in the U.K., the U.S. and other countries to bring about greater transparency in the ownership of the firms they incorporate (...)

 

http://knowledge.wharton.upenn.edu/article/confalon-nichols-panama-papers/

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The Formation of Social Conventions in Real-Time Environments

Why are some behaviors governed by strong social conventions while others are not? We experimentally investigate two factors contributing to the formation of conventions in a game of impure coordination: the continuity of interaction within each round of play (simultaneous vs. real-time) and the stakes of the interaction (high vs. low differences between payoffs). To maximize efficiency and fairness in this game, players must coordinate on one of two equally advantageous equilibria. In agreement with other studies manipulating continuity of interaction, we find that players who were allowed to interact continuously within rounds achieved outcomes with greater efficiency and fairness than players who were forced to make simultaneous decisions. However, the stability of equilibria in the real-time condition varied systematically and dramatically with stakes: players converged on more stable patterns of behavior when stakes are high. To account for this result, we present a novel analysis of the dynamics of continuous interaction and signaling within rounds. We discuss this previously unconsidered interaction between within-trial and across-trial dynamics as a form of social canalization. When stakes are low in a real-time environment, players can satisfactorily coordinate ‘on the fly’, but when stakes are high there is increased pressure to establish and adhere to shared expectations that persist across rounds.

 

Hawkins RXD, Goldstone RL (2016) The Formation of Social Conventions in Real-Time Environments. PLoS ONE 11(3): e0151670. http://dx.doi.org/10.1371/journal.pone.0151670

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Beyond Viral

The golden age of social media coincides with a worldwide leadership crisis, manifested by our seeming inability to address any major global issue in recent years.32 These days, no one—be they a charismatic leader or a nameless crowd—seems to be able to make issues popular for long enough to mobilize society into action. As a result of this leadership vacuum, social progress of all sorts seems to have become stymied and frozen. How can this happen precisely in a time when social media, praised as the ultimate tool to raise collective awareness and mobilize society, has reached maturity and widespread use? Here, we argue the coexistence of social media technologies with 'The End of Power'18 is anything but a coincidence, presenting the first techno-social paradox of the 21st century.

 

Beyond Viral
By Manuel Cebrian, Iyad Rahwan, Alex "Sandy" Pentland
Communications of the ACM, Vol. 59 No. 4, Pages 36-39
http://dx.doi.org/10.1145/2818992

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A general framework for measuring system complexity

In this work, we are motivated by the observation that previous considerations of appropriate complexity measures have not directly addressed the fundamental issue that the complexity of any particular matter or thing has a significant subjective component in which the degree of complexity depends on available frames of reference. Any attempt to remove subjectivity from a suitable measure therefore fails to address a very significant aspect of complexity. Conversely, there has been justifiable apprehension toward purely subjective complexity measures, simply because they are not verifiable if the frame of reference being applied is in itself both complex and subjective. We address this issue by introducing the concept of subjective simplicity—although a justifiable and verifiable value of subjective complexity may be difficult to assign directly, it is possible to identify in a given context what is “simple” and, from that reference, determine subjective complexity as distance from simple. We then propose a generalized complexity measure that is applicable to any domain, and provide some examples of how the framework can be applied to engineered systems.

 

A general framework for measuring system complexity
Mahmoud Efatmaneshnik and Michael J. Ryan

Complexity

http://dx.doi.org/10.1002/cplx.21767

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