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Complicity: An International Journal of Complexity and Education

Complicity: An International Journal of Complexity and Education | Social Simulation | Scoop.it

Complicity is an open access (free to all readers), peer-reviewed journal that publishes original articles on all aspects of education that are informed by the idea of complexity (in its technical, applied, philosophical, theoretical, or narrative manifestations). The journal strives to serve as a forum for both theoretical and practical contributions and to facilitate the exchange of diverse ideas and points of view related to complexity in education.


Via Complex Systems Digital Campus, Complexity Digest
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Social Simulation
News about social simulation, social networks dynamics and complex systems
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Nicolas Lassabe propage l'esprit fablab

Nicolas Lassabe propage l'esprit fablab | Social Simulation | Scoop.it
Qu'ils soient plutôt entrepreneurs ou scientifiques de haut vol, agitateurs d'idées ou orchestrateurs de talent, passionnés de technique ou fins analystes de ses usages, les cinquante pesonnalités dont nous vous proposons de découvrir le portrait jouent un rôle majeur dans l'innovation en France. C'est le cas du "maker" Nicolas Lassabe.

Via Université Toulouse 1 Capitole
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Université Toulouse 1 Capitole's curator insight, February 18, 3:11 AM

Diplômé de l'université Bordeaux I, Paul Sabatier et Toulouse I, le docteur en informatique Nicolas Lassabe, qui a été ingénieur chez Geosignal, entre 2004 et 2006, aime transmettre ce qu'il sait. Il a d'ailleurs enseigné pendant deux ans à l'université des sciences sociales de Toulouse jusqu'en 2008, avant de passer 7 mois à la faculté de Cornell pour faire de la recherche post-doctorale. C'est là qu'il découvre l’impression 3D, l’open-hardware et les fabLabs. Pour partager cette découverte, il crée en 2009 à Toulouse Artilect, le premier fabLab français.

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Science vs Conspiracy: Collective Narratives in the Age of Misinformation

Science vs Conspiracy: Collective Narratives in the Age of Misinformation | Social Simulation | Scoop.it
The large availability of user provided contents on online social media facilitates people aggregation around shared beliefs, interests, worldviews and narratives. In spite of the enthusiastic rhetoric about the so called collective intelligence unsubstantiated rumors and conspiracy theories—e.g., chemtrails, reptilians or the Illuminati—are pervasive in online social networks (OSN). In this work we study, on a sample of 1.2 million of individuals, how information related to very distinct narratives—i.e. main stream scientific and conspiracy news—are consumed and shape communities on Facebook. Our results show that polarized communities emerge around distinct types of contents and usual consumers of conspiracy news result to be more focused and self-contained on their specific contents. To test potential biases induced by the continued exposure to unsubstantiated rumors on users’ content selection, we conclude our analysis measuring how users respond to 4,709 troll information—i.e. parodistic and sarcastic imitation of conspiracy theories. We find that 77.92% of likes and 80.86% of comments are from users usually interacting with conspiracy stories.

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Origin of Peer Influence in Social Networks

Social networks pervade our everyday lives: we interact, influence, and are influenced by our friends and acquaintances. With the advent of the World Wide Web, large amounts of data on social networks have become available, allowing the quantitative analysis of the distribution of information on them, including behavioral traits and fads. Recent studies of correlations among members of a social network, who exhibit the same trait, have shown that individuals influence not only their direct contacts but also friends’ friends, up to a network distance extending beyond their closest peers. Here, we show how such patterns of correlations between peers emerge in networked populations. We use standard models (yet reflecting intrinsically different mechanisms) of information spreading to argue that empirically observed patterns of correlation among peers emerge naturally from a wide range of dynamics, being essentially independent of the type of information, on how it spreads, and even on the class of underlying network that interconnects individuals. Finally, we show that the sparser and clustered the network, the more far reaching the influence of each individual will be.
DOI: http://dx.doi.org/10.1103/PhysRevLett.112.098702

Origin of Peer Influence in Social Networks
Phys. Rev. Lett. 112, 098702 – Published 6 March 2014
Flávio L. Pinheiro, Marta D. Santos, Francisco C. Santos, and Jorge M. Pacheco


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Eli Levine's curator insight, March 10, 2014 5:16 PM

Indeed, we are all interconnected in very profound and subtle ways, whether we accept it or not.


This one's for the Libertarians and conservatives out there, who don't seem to think that their actions effect the other, or that the other can effect them, or that the actions done onto the other will effect the actions that are done onto them by the other.

 

Kind of like how they blame the poor for being angry at the rich, after the poor produced the wealth that engorges the rich.

 

Silly people....

 

Think about it.

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The Relative Ineffectiveness of Criminal Network Disruption : Scientific Reports : Nature Publishing Group

The Relative Ineffectiveness of Criminal Network Disruption : Scientific Reports : Nature Publishing Group | Social Simulation | Scoop.it
Researchers, policymakers and law enforcement agencies across the globe struggle to find effective strategies to control criminal networks. The effectiveness of disruption strategies is known to depend on both network topology and network resilience. However, as these criminal networks operate in secrecy, data-driven knowledge concerning the effectiveness of different criminal network disruption strategies is very limited. By combining computational modeling and social network analysis with unique criminal network intelligence data from the Dutch Police, we discovered, in contrast to common belief, that criminal networks might even become ‘stronger’, after targeted attacks. On the other hand increased efficiency within criminal networks decreases its internal security, thus offering opportunities for law enforcement agencies to target these networks more deliberately. Our results emphasize the importance of criminal network interventions at an early stage, before the network gets a chance to (re-)organize to maximum resilience. In the end disruption strategies force criminal networks to become more exposed, which causes successful network disruption to become a long-term effort.
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ECCS'14 European Conference on Complex Systems

ECCS'14 European Conference on Complex Systems | Social Simulation | Scoop.it

ECCS’14 will be a major international conference and event in the area of complex systems and interdisciplinary science in general. It will offer unique opportunities to study novel scientific approaches in a multitude of application areas. Two days of the conference, 24 and 25 of September, are reserved for satellite meetings, which will cover a broad range of subjects on all aspects of Complex Systems, as reflected by the conference tracks.

 

ECCS'14 European Conference on Complex Systems

Lucca, Italy

2014-09-22:26

http://www.eccs14.eu


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António F Fonseca's curator insight, January 16, 2014 12:02 PM

The major conference in Complex Systems this year will be held in Lucca.

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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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US Military Scientists Solve the Fundamental Problem of Viral Marketing | MIT Technology Review

US Military Scientists Solve the Fundamental Problem of Viral Marketing  | MIT Technology Review | Social Simulation | Scoop.it
Network theorists working for the US military have worked out how to identify the small “seed” group of people who can spread a message across an entire network

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António F Fonseca's curator insight, January 6, 2014 3:08 AM

It was already seaked by other groups, they only got sub-modularity properties defining the scope of greedy algorithm's search, these guys seem to be on the right track.

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Artificial Economics 2014 - AE 2014

The main aim of the Symposium is to facilitate the meeting of people working on different topics in different fields (mainly Economics, Finance and Computer Science) in order to encourage a structured multi-disciplinary approach to social sciences. Presentations and keynote sessions center around multi-agent modelling, from the viewpoint of both applications and computer-based tools. The event is also open to methodological surveys.

The event will be hosted by Social Simulation 2014, the 10th Conference of the European Social Simulation Association at the Universitat Autonoma de Barcelona, Barcelona, Spain.
September 1-5th, 2014.

http://essa2014.org


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ComplexInsight's curator insight, December 11, 2013 6:50 AM

bookmarking so can come back and read later.

ComplexInsight's curator insight, January 2, 2014 3:43 AM

Understanding how to simulate economic and social systems will be critical in future planning and analysis tools- The Social Simulation 2014 conference will be a key event. 

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Early-warning signals of topological collapse in interbank networks

The financial crisis clearly illustrated the importance of characterizing the level of ‘systemic’ risk associated with an entire credit network, rather than with single institutions. However, the interplay between financial distress and topological changes is still poorly understood. Here we analyze the quarterly interbank exposures among Dutch banks over the period 1998–2008, ending with the crisis. After controlling for the link density, many topological properties display an abrupt change in 2008, providing a clear – but unpredictable – signature of the crisis. By contrast, if the heterogeneity of banks' connectivity is controlled for, the same properties show a gradual transition to the crisis, starting in 2005 and preceded by an even earlier period during which anomalous debt loops could have led to the underestimation of counter-party risk. These early-warning signals are undetectable if the network is reconstructed from partial bank-specific data, as routinely done. We discuss important implications for bank regulatory policies.


Via Claudia Mihai, Complexity Digest
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Big Data needs Big Theory

Big Data needs Big Theory | Social Simulation | Scoop.it
In this guest cross-post, Geoffrey West, former President of the Santa Fe Institute, argues that just as the industrial age produced the laws of thermodynamics, we need universal laws of complexity...

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Jacek Bugajski's curator insight, November 25, 2013 4:26 AM

Big Data needs Big Theory

Ricardo Pimenta's curator insight, December 4, 2013 8:32 AM

Big theory is needed to Big Data issues...

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The Math of Segregation

The Math of Segregation | Social Simulation | Scoop.it

In the 1960s Schelling devised a simple model in which a mixed group of people spontaneously segregates by race even though no one in the population desires that outcome. Initially, black and white families are randomly distributed. At each step in the modeling process the families examine their immediate neighborhood and either stay put or move elsewhere depending on whether the local racial composition suits their preferences. The procedure is repeated until everyone finds a satisfactory home (or until the simulator’s patience is exhausted).


Via Bernard Ryefield, Complexity Digest, Ashish Umre
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An Introduction to Community Detection in Multi-layered Social Network

Piotr Bródka, Tomasz Filipowski, Przemysław Kazienko
(Submitted on 26 Sep 2012)
Social communities extraction and their dynamics are one of the most important problems in today's social network analysis. During last few years, many researchers have proposed their own methods for group discovery in social networks. However, almost none of them have noticed that modern social networks are much more complex than few years ago. Due to vast amount of different data about various user activities available in IT systems, it is possible to distinguish the new class of social networks called multi-layered social network. For that reason, the new approach to community detection in the multi-layered social network, which utilizes multi-layered edge clustering coefficient is proposed in the paper.

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How People Interact in Evolving Online Affiliation Networks

How People Interact in Evolving Online Affiliation Networks | Social Simulation | Scoop.it

The concept of social networks, in the age of Twitter and Facebook, seems like a really banal one. Social networks, however, have turned out to be a fertile ground for scientific studies of human interactions by not only social scientists, but also by physicists, from which we gain illuminating insights about ourselves and our societies. For example, why, and how, do we make new friends or establish fresh social ties? In this paper, we show that meaningful answers to these questions can be learned, by bringing concepts and methods from statistical physics to bear in a new analysis of the detailed growth dynamics of two networks associated with two online social-networking sites.

 

How People Interact in Evolving Online Affiliation Networks

Lazaros K. Gallos, Diego Rybski, Fredrik Liljeros, Shlomo Havlin, and Hernán A. Makse


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Advances in Artificial Economics

Advances in Artificial Economics | Social Simulation | Scoop.it

The interactions between Computer Science and the Social Sciences have grown fruitfully along the past 20 years. The mutual benefits of such a cross-fertilization stand as well at a conceptual, technological or methodological level. Economics in particular benefited from innovations in multi-agent systems in Computer Science leading to agent-based computational economics and in return the multi-agent systems benefited for instance of economic researches related to mechanisms of incentives and regulation to design self-organized systems. Created 10 years ago, in 2005 in Lille (France) by Philippe Matthieu and his team, the Artificial Economics conference series reveals the liveliness of the collaborations and exchanges among computer scientists and economists in particular. The excellent quality of this conference has been recognized since its inception and its proceedings have been regularly published in Springer’s Lecture Notes in Economics and Mathematical Systems series. At about the same period, the European Social Simulation Association was created and decided to support an annual conference dedicated to computational approaches of the social sciences. Both communities kept going alongside for the past ten years presenting evident overlaps concerning either their approaches or their members. This year, both conferences have decided to join their efforts and hold a common conference, Social Simulation Conference, in Barcelona, Spain, 1st to 5th September 2014 which will host the 10th edition of the Artificial Economics Conference. In this edition, 32 submissions from 11 countries were received, from which we selected 20 for presentation (near 60 % acceptance). The papers have then been revised and extended and 19 papers were selected in order to make part of this volume.


Via Jorge Louçã, NESS
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Data Mining Indian Recipes Reveals New Food Pairing Phenomenon

Data Mining Indian Recipes Reveals New Food Pairing Phenomenon | Social Simulation | Scoop.it
The food pairing hypothesis is the idea that ingredients that share the same flavors ought to combine well in recipes. For example, the English chef Heston Blumenthal discovered that white chocolate and caviar share many flavors and turn out to be a good combination. Other unusual combinations that seem to confirm the hypothesis include strawberries and peas, asparagus and butter, and chocolate and blue cheese.

But in recent years researchers have begun to question how well this hypothesis holds in different cuisines. For example, food pairing seems to be common in North American and Western European cuisines but absent in cuisines from southern Europe and East Asia.

Today, Anupam Jain and pals at the Indian Institute of Technology Jodhpur say the opposite effect occurs in Indian cuisine. In this part of the world, foods with common flavors are less likely to appear together in the same recipe. And the presence of certain spices make the negative food pairing effect even stronger.

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avocetnail's comment, February 28, 12:40 AM
Its fabulous :)
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Spatially Distributed Social Complex Networks

We propose a bare-bones stochastic model that takes into account both the geographical distribution of people within a country and their complex network of connections. The model, which is designed to give rise to a scale-free network of social connections and to visually resemble the geographical spread seen in satellite pictures of the Earth at night, gives rise to a power-law distribution for the ranking of cities by population size (but for the largest cities) and reflects the notion that highly connected individuals tend to live in highly populated areas. It also yields some interesting insights regarding Gibrat’s law for the rates of city growth (by population size), in partial support of the findings in a recent analysis of real data [Rozenfeld et al., Proc. Natl. Acad. Sci. U.S.A. 105 18702 (2008)]. The model produces a nontrivial relation between city population and city population density and a superlinear relationship between social connectivity and city population, both of which seem quite in line with real data.
DOI: http://dx.doi.org/10.1103/PhysRevX.4.011008

Spatially Distributed Social Complex Networks
Phys. Rev. X 4, 011008 – Published 28 January 2014
Gerald F. Frasco, Jie Sun, Hernán D. Rozenfeld, and Daniel ben-Avraham


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Twitter Trends Help Researchers Forecast Viral Memes

Twitter Trends Help Researchers Forecast Viral Memes | Social Simulation | Scoop.it

What makes a meme— an idea, a phrase, an image—go viral? For starters, the meme must have broad appeal, so it can spread not just within communities of like-minded individuals but can leap from one community to the next. Researchers, by mining public Twitter data, have found that a meme's “virality” is often evident from the start. After only a few dozen tweets, a typical viral meme (as defined by tweets using a given hashtag) will already have caught on in numerous communities of Twitter users. In contrast, a meme destined to peter out will resonate in fewer groups.

 


Via Claudia Mihai, Complexity Digest
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june holley's curator insight, January 23, 2014 8:31 AM

Some important ideas here for people interested in change.

Premsankar Chakkingal's curator insight, January 30, 2014 8:58 AM

Forecasting the Future Twitter Trends in hashtags

Christian Verstraete's curator insight, February 3, 2014 4:48 AM

Twitter, what happens when things go viral?

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Complicity: An International Journal of Complexity and Education

Complicity: An International Journal of Complexity and Education | Social Simulation | Scoop.it

Complicity is an open access (free to all readers), peer-reviewed journal that publishes original articles on all aspects of education that are informed by the idea of complexity (in its technical, applied, philosophical, theoretical, or narrative manifestations). The journal strives to serve as a forum for both theoretical and practical contributions and to facilitate the exchange of diverse ideas and points of view related to complexity in education.


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Towards Passive Political Opinion Polling using Twitter

Social media platforms, such as Twitter, provide a forum for political communication where politicians broadcast messages and where the general public engages in the discussion of pertinent political issues. The open nature of Twitter, together with its large volume of traffic, makes it a useful resource for new forms of ‘passive’ opinion polling , i.e. automatically monitoring and detecting which key issues the general public is concerned about and inferring their voting intentions. In this paper, we present a number of case studies for the automatic analysis of UK political tweets. We investigate the automated sentiment analysis of tweets from UK Members of Parliament (MPs) towards the main political parties. We then investigate using the volume and sentiment of the tweets from other users as a proxy for their voting intention and compare the results against existing poll data. Finally we conduct automatic identification of the key topics discussed by both the MPs and users on Twitter and compare them with the main political issues identified in traditional opinion polls. We describe our data collection methods, analysis tools and evaluation framework and discuss our results and the factors affecting their accuracy.


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M. Edward (Ed) Borasky's curator insight, January 6, 2014 7:15 PM

For a variety of statistical reasons I'm skeptical, but this is an important research area so I'm posting this.

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Efficient discovery of overlapping communities in massive networks

Efficient discovery of overlapping communities in massive networks | Social Simulation | Scoop.it

Detecting overlapping communities is essential to analyzing and exploring natural networks such as social networks, biological networks, and citation networks. However, most existing approaches do not scale to the size of networks that we regularly observe in the real world. In this paper, we develop a scalable approach to community detection that discovers overlapping communities in massive real-world networks. Our approach is based on a Bayesian model of networks that allows nodes to participate in multiple communities, and a corresponding algorithm that naturally interleaves subsampling from the network and updating an estimate of its communities. We demonstrate how we can discover the hidden community structure of several real-world networks, including 3.7 million US patents, 575,000 physics articles from the arXiv preprint server, and 875,000 connected Web pages from the Internet. Furthermore, we demonstrate on large simulated networks that our algorithm accurately discovers the true community structure. This paper opens the door to using sophisticated statistical models to analyze massive networks.


Via Claudia Mihai, Complexity Digest
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ComplexInsight's curator insight, December 31, 2013 4:02 AM

Network visualization tools like Gephi and analysis tools like SNAP are becoming essential components in understanding, mapping and comprehending inter-relating networks and network processes. This is a good paper that gives insight into appliying networking analysis tools to identify otherwise hidden community structures in apparhently disconnected or partially connected sets which will be hugely important in large scale network analysis.

Investors Europe Stock Brokers's curator insight, September 1, 2014 2:14 AM

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Subliminal Influence or Plagiarism by Negligence? The Slodderwetenschap of Ignoring the Internet

Does the availability of instant reference checking and “find more like this” research on the Internet change the standards by which academics should feel “obligated” to cite the work of others? Is the deliberate refusal to look for the existence of parallel work by others an ethical lapse or merely negligence? At a minimum, the Dutch standard of Slodderwetenschap (sloppy science) is clearly at work. At a maximum so is plagiarism. In between sits the process to be labeled as ‘plagiarism by negligence’. This article seeks to expose the intellectual folly of allowing such a plagiarism to be tolerated by the academy through a discussion of the cases of Terrence Deacon and Stephen Wolfram.

 

Subliminal Influence or Plagiarism by Negligence? The Slodderwetenschap of Ignoring the Internet

Michael Lissack

http://isce.edu/Subliminal.pdf


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Arjen ten Have's comment, December 4, 2013 2:01 PM
The Dutch standard of Slodderwetenschap? Bit sloppy, it is a recent Dutch word, hope not ths standard.
Ellie Kesselman Wells's comment, December 5, 2013 4:43 PM
Excellent subject matter! Thank you!
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Complex Systems Science as a New Transdisciplinary Science, by Paul Bourgine

The new science of complex systems will be at the heart of the future of the Worldwide Knowledge Society. It is providing radical new ways of understanding the physical, biological, ecological, and techno-social universe. Complex Systems are open, value-laden, multi-level, multi-component, reconfigurable systems of systems, situated in turbulent, unstable, and changing environments. They evolve, adapt and transform through internal and external dynamic interactions. They are the source of very difficult scientific challenges for observing, understanding, reconstructing and predicting their multi-scale dynamics. The challenges posed by the multi-scale modelling of both natural and artificial adaptive complex systems can only be met with radically new collective strategies for research and teaching (...)


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june holley's curator insight, December 2, 2013 10:39 AM

The study of complex systems adds a lot of depth to understanding networks.

Complexity Institute's curator insight, December 6, 2013 3:56 AM

Are we ready to recognize a Science as a "Transdisciplinary Science?
Complex systems science is not a science in itself, but it may be considered as a 'Science of Sciences'.
I think this is the most challenging issue to face for a Worldwide Knowledge Society, as Paul Bourgine states.
What are your opinions about this?

Edgar Francisco Pelayo Valencia's curator insight, December 20, 2013 5:26 PM

Future is here!!!

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[1311.3674] Evolutionary perspectives on collective decision making: Studying the implications of diversity and social network structure with agent-based simulations


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Social Network Size Linked to Brain Size

Social Network Size Linked to Brain Size | Social Simulation | Scoop.it
How and why the volume of the orbital prefrontal cortex is related to the size of social networks...

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Viktoras Veitas's comment, September 1, 2012 12:47 PM
The idea came across my mind wile reading this. Global Brain can be compared to a global social network (= giant global graph). Humans are not able to form a meaningfull social network with more than 150 members. Global Brain should encompass the whole humanity, i.e. in the order of billions. So, in order for the Global Brain to emerge, we need (1) to either enhance humans to be able to form "theories of mind" of this magnitude, or, alternatively, (2) to create artificial agents, capable of doing this and connecting humans. Oh, and there is a third way - doing both in parallel...