The annual European Conferences on Complex Systems (ECCS) have become a major venue for the Complex Systems Community since they were started in 2003. For the first time, this year, the conference will be held in North America to foster and multiply contacts between the European, North American and Asian communities working in this domain. CCS’15 will be a major international conference and event in the area of complex systems and interdisciplinary science in general.
The conference will offer unique opportunities to study novel scientific approaches in a multitude of application areas, as reflected by the conference tracks:
Conference Main Tracks
Foundations of Complex Systems (complex networks, self-organization, nonlinear dynamics, statistical physics, mathematical modeling, simulation)Information and Communication Technologies (Internet, WWW, search, semantic web)Language, Linguistics, Cognition and Social Systems (evolution of language, social consensus, artificial intelligence, cognitive processes)Economics and Finance (social networks, game theory, stock market, crises)Infrastructure, Planning and Environment (critical infrastructures, urban planning, mobility, transport, energy)Biological Complexity (biological networks, systems biology, evolution, natural science, medicine and physiology)Social Ecological Systems (global environmental change, green growth, sustainability, resilience)
The question What is Complexity? has occupied a great deal of time and paper over the last 20 or so years. There are a myriad different perspectives and definitions but still no consensus. In this paper I take a phenomenological approach, identifying several factors that discriminate well between systems that would be consensually agreed to be simple versus others that would be consensually agreed to be complex - biological systems and human languages. I argue that a crucial component is that of structural building block hierarchies that, in the case of complex systems, correspond also to a functional hierarchy. I argue that complexity is an emergent property of this structural/functional hierarchy, induced by a property - fitness in the case of biological systems and meaning in the case of languages - that links the elements of this hierarchy across multiple scales. Additionally, I argue that non-complex systems "are" while complex systems "do" so that the latter, in distinction to physical systems, must be described not only in a space of states but also in a space of update rules (strategies) which we do not know how to specify. Further, the existence of structural/functional building block hierarchies allows for the functional specialisation of structural modules as amply observed in nature. Finally, we argue that there is at least one measuring apparatus capable of measuring complexity as characterised in the paper - the human brain itself.
The six funders of the Centre for Evaluating Complexity across the Energy-Environment-Food Nexus held a ‘bidders launch event‘ on 11 February 2015 in London, for people with an interest in bidding to run the centre.
The Centre will pioneer, test and promote innovative and inclusive methods to analyse evaluations across the energy-environment-food nexus where complexity presents an integral challenge to policy interventions.
Much less is known about the development of the social sciences as a complete discipline group than about the previously dominant STEM (science, technology, engineering and mathematics) discipline group. Patrick Dunleavy, Simon Bastow and Jane Tinkler set out some key findings from their new book ‘The Impacts of the Social Sciences’, identifying five key trends that are causing the old social sciences versus physical science divide to dissolve. With the advent of ‘big data’ and e-science across the board, the social sciences are converging strongly on a ‘rapid advance/moderate consensus’ model previously characteristic only of the STEM disciplines.
The faculty job market plays a fundamental role in shaping research priorities, educational outcomes, and career trajectories among scientists and institutions. However, a quantitative understanding of faculty hiring as a system is lacking. Using a simple technique to extract the institutional prestige ranking that best explains an observed faculty hiring network—who hires whose graduates as faculty—we present and analyze comprehensive placement data on nearly 19,000 regular faculty in three disparate disciplines. Across disciplines, we find that faculty hiring follows a common and steeply hierarchical structure that reflects profound social inequality. Furthermore, doctoral prestige alone better predicts ultimate placement than a U.S. News & World Report rank, women generally place worse than men, and increased institutional prestige leads to increased faculty production, better faculty placement, and a more influential position within the discipline. These results advance our ability to quantify the influence of prestige in academia and shed new light on the academic system.
Systematic inequality and hierarchy in faculty hiring networks Aaron Clauset, Samuel Arbesman, Daniel B. Larremore
Science Advances 01 Feb 2015: Vol. 1 no. 1 e1400005
In this paper, we review some advances made recently in the study of mobile phone datasets. This area of research has emerged a decade ago, with the increasing availability of large-scale anonymized datasets, and has grown into a stand-alone topic. We will survey the contributions made so far on the social networks that can be constructed with such data, the study of personal mobility, geographical partitioning, urban planning, and help towards development as well as security and privacy issues.
A survey of results on mobile phone datasets analysis Vincent D. Blondel, Adeline Decuyper, Gautier Krings
To maintain stability yet retain the flexibility to adapt to changing circumstances, social systems must strike a balance between the maintenance of a shared reality and the survival of minority opinion. A computational model is presented that investigates the interplay of two basic, oppositional social processes—conformity and anticonformity—in promoting the emergence of this balance. Computer simulations employing a cellular automata platform tested hypotheses concerning the survival of minority opinion and the maintenance of system stability for different proportions of anticonformity. Results revealed that a relatively small proportion of anticonformists facilitated the survival of a minority opinion held by a larger number of conformists who would otherwise succumb to pressures for social consensus. Beyond a critical threshold, however, increased proportions of anticonformists undermined social stability. Understanding the adaptive benefits of balanced oppositional forces has implications for optimal functioning in psychological and social processes in general.
The Critical Few: Anticonformists at the Crossroads of Minority Opinion Survival and Collapse by Matthew Jarman, Andrzej Nowak, Wojciech Borkowski, David Serfass, Alexander Wong and Robin Vallacher http://jasss.soc.surrey.ac.uk/18/1/6.html
On Saturday, April 18th, experience mathematics like never before, when the first-of-its-kind National Math Festival comes to Washington, D.C. As the country’s first national festival dedicated to discovering the delight and power of mathematics, this free and public celebration will feature dozens of activities for every age—from hands-on magic, a scavenger hunt, and Houdini-like getaways, to lectures with some of the most influential mathematicians of our time.
The National Math Festival is organized by the Mathematical Sciences Research Institute (MSRI) and the Institute for Advanced Study (IAS) in cooperation with the Smithsonian Institution.
We investigate the laws governing people’s decisions and interactions by studying the collective dynamics of a well-documented social activity for which there exist ample records of the perceived quality: the attendance to movie theaters in the US. We picture the flows of attendance as impulses or “shocks” driven by external factors that in turn can create new cascades of attendances through direct recommendations whose effectiveness depends on the perceived quality of the movies. This corresponds to an epidemic branching model comprised of a decaying exponential function determining the time between cause and action, and a cascade of actions triggered by previous ones. We find that the vast majority of the ~3,500 movies studied fit our model remarkably well. From our results, we are able to translate a subjective concept such as movie quality into a probability of the deriving individual activity, and from it we build concrete quantitative predictions. Our analysis opens up the possibility of understanding other collective dynamics for which the perceived quality or appeal of an action is also known.
The gender imbalance in STEM subjects dominates current debates about women’s underrepresentation in academia. However, women are well represented at the Ph.D. level in some sciences and poorly represented in some humanities (e.g., in 2011, 54% of U.S. Ph.D.’s in molecular biology were women versus only 31% in philosophy). We hypothesize that, across the academic spectrum, women are underrepresented in fields whose practitioners believe that raw, innate talent is the main requirement for success, because women are stereotyped as not possessing such talent. This hypothesis extends to African Americans’ underrepresentation as well, as this group is subject to similar stereotypes. Results from a nationwide survey of academics support our hypothesis (termed the field-specific ability beliefs hypothesis) over three competing hypotheses.
Expectations of brilliance underlie gender distributions across academic disciplines Sarah-Jane Leslie, Andrei Cimpian, Meredith Meyer, Edward Freeland
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.
What will be the growth of the Gross Domestic Product (GDP) or the competitiveness of China, United States, and Vietnam in the next 3, 5 or 10 years? Despite this kind of questions has a large societal impact and an extreme value for economic policy making, providing a scientific basis for economic predictability is still a very challenging problem. Recent results of a new branch—Economic Complexity—have set the basis for a framework to approach such a challenge and to provide new perspectives to cast economic prediction into the conceptual scheme of forecasting the evolution of a dynamical system as in the case of weather dynamics. We argue that a recently introduced non-monetary metrics for country competitiveness (fitness) allows for quantifying the hidden growth potential of countries by the means of the comparison of this measure for intangible assets with monetary figures, such as GDP per capita . This comparison defines the fitness-income plane where we observe that country dynamics presents strongly heterogeneous patterns of evolution. The flow in some zones is found to be laminar while in others a chaotic behavior is instead observed. These two regimes correspond to very different predictability features for the evolution of countries: in the former regime, we find strong predictable pattern while the latter scenario exhibits a very low predictability. In such a framework, regressions, the usual tool used in economics, are no more the appropriate strategy to deal with such a heterogeneous scenario and new concepts, borrowed from dynamical systems theory, are mandatory. We therefore propose a data-driven method— the selective predictability scheme —in which we adopt a strategy similar to the methods of analogues , firstly introduced by Lorenz, to assess future evolution of countries.
Matthieu Cristelli , Andrea Tacchella, Luciano Pietronero
One question that social scientists and economists have long puzzled over is how corruption arises in different cultures and why it is more prevalent in some countries than others. But it has always been difficult to find correlations between corruption and other measures of economic or social activity.
Michal Paulus and Ladislav Kristoufek at Charles University in Prague, Czech Republic have for the first time found a correlation between the perception of corruption in different countries and their economic development.
The data they use comes from Transparency International, a non-profit campaigning organisation based in Berlin, Germany, and which defines corruption as the misuse of public power for private benefit. Each year, this organisation publishes a global list of countries ranked according to their perceived levels of corruption. The list is compiled using at least three sources of information but does not directly measure corruption, because of the difficulties in gathering such data.
When the euro crisis began a half-decade ago, Keynesian economists predicted that the austerity imposed on Greece and the other crisis countries would fail. Now that it has, what is needed is not structural reform in Greece so much as a fundamental reform of the eurozone's design and policy frameworks.
He’d been born into a tough family in Prohibition-era Detroit, where his father, a boiler-maker, had no trouble raising his fists to get his way. The neighborhood boys weren’t much better. One afternoon in 1935, they chased him through the streets until he ducked into the local library to hide. The library was familiar ground, where he had taught himself Greek, Latin, logic, and mathematics—better than home, where his father insisted he drop out of school and go to work. Outside, the world was messy. Inside, it all made sense.
Not wanting to risk another run-in that night, Pitts stayed hidden until the library closed for the evening. Alone, he wandered through the stacks of books until he came across Principia Mathematica, a three-volume tome written by Bertrand Russell and Alfred Whitehead between 1910 and 1913, which attempted to reduce all of mathematics to pure logic. Pitts sat down and began to read. For three days he remained in the library until he had read each volume cover to cover—nearly 2,000 pages in all—and had identified several mistakes. Deciding that Bertrand Russell himself needed to know about these, the boy drafted a letter to Russell detailing the errors. Not only did Russell write back, he was so impressed that he invited Pitts to study with him as a graduate student at Cambridge University in England. Pitts couldn’t oblige him, though—he was only 12 years old. But three years later, when he heard that Russell would be visiting the University of Chicago, the 15-year-old ran away from home and headed for Illinois. He never saw his family again. (...)
Studies using massive, passively data collected from communication technologies have revealed many ubiquitous aspects of social networks, helping us understand and model social media, information diffusion, and organizational dynamics. More recently, these data have come tagged with geographic information, enabling studies of human mobility patterns and the science of cities. We combine these two pursuits and uncover reproducible mobility patterns amongst social contacts. First, we introduce measures of mobility similarity and predictability and measure them for populations of users in three large urban areas. We find individuals' visitations patterns are far more similar to and predictable by social contacts than strangers and that these measures are positively correlated with tie strength. Unsupervised clustering of hourly variations in mobility similarity identifies three categories of social ties and suggests geography is an important feature to contextualize social relationships. We find that the composition of a user's ego network in terms of the type of contacts they keep is correlated with mobility behavior. Finally, we extend a popular mobility model to include movement choices based on social contacts and compare it's ability to reproduce empirical measurements with two additional models of mobility.
by Jameson L. Toole, Carlos Herrera-Yague, Christian M. Schneider, Marta C. Gonzalez
After the Snowden revelations, U.S. mathematicians are questioning their long-standing ties with the secretive National Security Agency.
Each year, recruiters from the National Security Agency (NSA), said to be the largest employer of mathematicians in the United States, visit a few dozen universities across the country in search of new talent. It used to be an easy sell. “One of the appealing aspects that they pitch is that you'll be working on incredibly hard and interesting puzzles all day,” says one mathematician who requested anonymity. In the wake of the terrorist attacks of 11 September 2001, he adds, “I felt that if there was any way I could use my mathematical ability to prevent such a thing from ever happening again, I was morally obligated to do it.” Several times over the past decade, he has set aside his university research to work for the agency. (...)
NESS held a workshop on this theme with local policy makers in Rochdale, a borough in Greater Manchester. John Blundell is an elected local councillor and is Deputy Chairman of the Economic Regeneration Committee in Rochdale. Paul Ormerod is a member of the committee of the NESS project.
In this short paper, (available here: http://nessnet.eu/docs/NessRochdaleJuly2014.pdf), Blundell and Ormerod identify key principles of non-equilibrium, complexity based social science which are of direct policy relevance to relatively deprived, post-industrial towns across the EU, of which Rochdale is an example:
* Lock-in and path dependence. Once a local area becomes relatively deprived, this tends to persist for long periods of time
* Positive feedbacks. Agglomeration effects, namely the benefits which arise from high densities of employment in a local area, raise productivity levels across the local economy as a whole, and make it an even more attractive location for companies
* Resilience. The ability of a local economy to respond to shocks, whether general or specific, is an important issue. This is not a timeless phenomenon, in which we simply compare one equilibrium with the new one, the process by which this happens is crucial
* Tipping points. There is a critical mass of agglomeration, beyond which further rises in employment density bring considerably greater increases in productivity
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