Challenges in network science: Applications to infrastructures, climate, social systems and economics

Havlin, Shlomo; Kenett, Dror Y.; Ben‐Jacob, Eshel; Bunde, Armin; Cohen, Reuven; Hermann, H.; Kantelhardt, Jan W.; Kertész, János; Kirkpatrick, Scott; Kurths, Jürgen; Portugali, Juval; Solomon, Sorin

doi:10.1140/epjst/e2012-01695-x

Cited by 165 publications

(106 citation statements)

References 143 publications

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“…[38], financial systems are complex adaptive system, in which the micro interactions translate into macro dynamics through bottom-up mechanisms, followed by topdown feedback between the macro and the micro. In this paper we introduced a novel theoretical framework to describe financial market macro-dynamics in which single agents interact in non-linear and complex ways.…”

Section: Discussionmentioning

confidence: 99%

Financial Symmetry and Moods in the Market

2014

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This paper studies how certain speculative transitions in financial markets can be ascribed to a symmetry break that happens in the collective decision making. Investors are assumed to be bounded rational, using a limited set of information including past price history and expectation on future dividends. Investment strategies are dynamically changed based on realized returns within a game theoretical scheme with Nash equilibria. In such a setting, markets behave as complex systems whose payoff reflect an intrinsic financial symmetry that guarantees equilibrium in price dynamics (fundamentalist state) until the symmetry is broken leading to bubble or anti-bubble scenarios (speculative state). We model such twophase transition in a micro-to-macro scheme through a Ginzburg-Landau-based power expansion leading to a market temperature parameter which modulates the state transitions in the market. Via simulations we prove that transitions in the market price dynamics can be phenomenologically explained by the number of traders, the number of strategies and amount of information used by agents, all included in our market temperature parameter.

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Section: Discussionmentioning

confidence: 99%

Financial Symmetry and Moods in the Market

2014

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“…Social networks, for example, are investigated by the properties they exhibit once they have emerged (e.g., scale-freeness). Instead, poor attention has been paid so far to the conditions favouring, and allowing to predict, the emergence of social networks (see [36] and later on in this paper, 4.1.2). Agent-based modellers have begun to address this issue and to study the link between fundamental behavioural processes, social conditions, and the macroscopic structure of emergent complex networks [37].…”

Section: Emergent Phenomena At the Aggregate Levelmentioning

confidence: 99%

Manifesto of computational social science

Conte

Gilbert

Bonelli

et al. 2012

Eur. Phys. J. Spec. Top.

333

224

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Abstract. The increasing integration of technology into our lives has created unprecedented volumes of data on society's everyday behaviour. Such data opens up exciting new opportunities to work towards a quantitative understanding of our complex social systems, within the realms of a new discipline known as Computational Social Science. Against a background of financial crises, riots and international epidemics, the urgent need for a greater comprehension of the complexity of our interconnected global society and an ability to apply such insights in policy decisions is clear. This manifesto outlines the objectives of this new scientific direction, considering the challenges involved in it, and the extensive impact on science, technology and society that the success of this endeavour is likely to bring about.

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“…Network science has greatly evolved in the twenty first century, and is currently a leading scientific field in the description of complex systems, which affects every aspect of our daily life [2,[22][23][24][25]. Network theory provides the means to model the functional structure of different spheres of interest, and thus, understanding more accurately the functioning of the network of relationships between the actors of the system, its dynamics and the scope or degree of influence.…”

Section: Cascading Failures In Economic Networkmentioning

confidence: 99%

“…The growth of technology, globalization, and urbanization has caused world-wide human social and economic activities to become increasingly interdependent [1][2][3][4][5][6][7][8][9][10][11][12][13]. From the recent financial crisis it is clear that components of this complex system have become increasingly susceptible to collapse.…”

Section: Introductionmentioning

confidence: 99%

Cascading Failures in Interdependent Economic Networks

Havlin

Kenett

2015

Proceedings of the International Conference on Social Modeling and Simulation, Plus Econophysics Colloquium 2014

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Throughout the past decade, there has been a significant advance in understanding the structure and function of networks, and mathematical models of networks are now widely used to describe a broad range of complex systems, such as socio-economic systems. However, the significant majority of methods have dealt almost exclusively with individual networks treated as isolated systems. In reality an individual network is often just one component in a much larger complex multi-level network (network of networks, NON). The NON framework provides critical new insights into the structure and function of real-world complex systems. One such insight is that NON system is significantly more vulnerable to shocks and damages, which has lead to the development of the theory of cascading failures in interdependent networks. Here we provide an overview of this theory, and one example of its application to economic systems. IntroductionThe growth of technology, globalization, and urbanization has caused world-wide human social and economic activities to become increasingly interdependent [1][2][3][4][5][6][7][8][9][10][11][12][13]. From the recent financial crisis it is clear that components of this complex system have become increasingly susceptible to collapse. Current models have been unable to predict instability, provide scenarios for future stability, or control or even mitigate systemic failure. Thus, there is a need of new ways of quantifying complex system vulnerabilities as well as new strategies for mitigating systemic damage and increasing system resiliency [14,15]. Achieving this would also provide new insight into such key issues as financial contagion [16,17] and systemic risk [18][19][20] and would provide a way of maintaining economic and financial stability in the future.

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Challenges in network science: Applications to infrastructures, climate, social systems and economics

Cited by 165 publications

References 143 publications

Financial Symmetry and Moods in the Market

Financial Symmetry and Moods in the Market

Manifesto of computational social science

Cascading Failures in Interdependent Economic Networks

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