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There is increasing societal and scholarly interest in understanding how social integration can be maintained in a diverse society. This paper takes a model of the relation between opinion polarization and ethnic segregation as an example for social complexity. Many argue that segregation between different groups in society fosters opinion polarization. Earlier modeling work has supported this theoretically. Here, a simple model is presented that generates the opposite prediction based on the assumption that influence can be assimilative or repulsive, depending on the discrepancy between interacting individuals. It is discussed that these opposite results from similar models point to the need for more empirical research into micro-level assumptions and the micro-to-macro transformation in models of opinion dynamics in a diverse society.

There is increasing societal and scholarly interest in understanding how social integration can be maintained in a diverse society. This paper takes a model of the relation between opinion polarization and ethnic segregation as an example for social complexity. Many argue that segregation between different groups in society fosters opinion polarization. Earlier modeling work has supported this theoretically. Here, a simple model is presented that generates the opposite prediction based on the assumption that influence can be assimilative or repulsive, depending on the discrepancy between interacting individuals. It is discussed that these opposite results from similar models point to the need for more empirical research into micro-level assumptions and the micro-to-macro transformation in models of opinion dynamics in a diverse society.

We present a new model for the diffusion of innovation. Here, the population is segmented into distinct groups. Adoption by a particular group of some cultural product may be inhibited both by large numbers of its own members already having adopted but also, in particular, by members of another group having adopted. Intergroup migration is also permitted. We determine the equilibrium points and carry out stability analysis for the model for a two-group population. We also simulate a discrete time version of the model. Lastly, we present data on tablet use in eight countries from 2012-2016 and show that the relationship between use in the "under 25" age group and "55+" age group conforms to the model.

Terrorism instills fear in the minds of people and takes away the freedom of individuals to act as they will. Terrorism has turned out to be an international menace today. Here, we study the terrorist attack incidents which occurred in the last half-century across the globe from the open source, Global Terrorism Database, and develop a view on their spatio-temporal dynamics. We construct a complex network of global terrorism and study its growth dynamics, along with the statistical properties of the anti-social network, which are quite intriguing. Normally, each nation pursues its own vision of international security based upon its mandate and particular notions of politics and its policies to counter the threat of terrorism that could naturally include the use of tactical measures and strategic negotiations, or even physical power. We study the network resilience against targeted attacks and random failures, which could guide the counterterrorist outfits in designing strategies to fight terrorism. We then use a disparity filter method to isolate backbone of the network, and identify the terror hubs and vulnerable motifs of global terrorism. We also examine evolution of the hubs and motifs in a few exemplary cases like Afghanistan, Colombia, India, Israel, Pakistan and the United Kingdom. The dynamics of the terror hubs and the vulnerable motifs that we discover in the network backbone turn out to be very significant, and may provide deep insight on their formations and spreading, and thereby help in contending terrorism or framing public policies that can check their spread., Comment: 33 pages, 11 figures, 5 tables

News reports in media contain records of a wide range of socio-economic and political events in time. Using a publicly available, large digital database of news records, and aggregating them over time, we study the network of ethnic conflicts and human rights violations. Complex network analyses of the events and the involved actors provide important insights on the engaging actors, groups, establishments and sometimes nations, pointing at their long range effect over space and time. We find power law decays in distributions of actor mentions, co-actor mentions and degrees and dominance of influential actors and groups. Most influential actors or groups form a giant connected component which grows in time, and is expected to encompass all actors globally in the long run. We demonstrate how targeted removal of actors may help stop spreading unruly events. We study the cause-effect relation between types of events, and our quantitative analysis confirm that ethnic conflicts lead to human rights violations, while it does not support the converse., Comment: 16 pages; main paper + Supplementary Information file; accepted for publication in Scientific Reports

In this article, we present a brief narration of the origin and the overview of the recent developments done on the Kolkata Paise Restaurant (KPR) problem, which can serve as a prototype for a broader class of resource allocation problems in the presence of a large number of competing agents, typically studied using coordination and anti-coordination games. We discuss the KPR and its several extensions, as well as its applications in many economic and social phenomena. We end the article with some discussions on our ongoing experimental analysis of the same problem. We demonstrate that this provides an interesting picture of how people analyze complex situations, and design their strategies or react to them., Comment: 14 pages, Submitted for publication in a special issue in Science and Culture (Kolkata, India)

Demand outstrips available resources in most situations, which gives rise to competition, interaction and learning. In this article, we review a broad spectrum of multi-agent models of competition (El Farol Bar problem, Minority Game, Kolkata Paise Restaurant problem, Stable marriage problem, Parking space problem and others) and the methods used to understand them analytically. We emphasize the power of concepts and tools from statistical mechanics to understand and explain fully collective phenomena such as phase transitions and long memory, and the mapping between agent heterogeneity and physical disorder. As these methods can be applied to any large-scale model of competitive resource allocation made up of heterogeneous adaptive agent with non-linear interaction, they provide a prospective unifying paradigm for many scientific disciplines.

This article is the second part of a review of recent empirical and theoretical developments usually grouped under the term Econophysics. In the first part, we have reviewed statistical properties of financial times series, statistics exhibited on order books and discussed some studies of correlations of assets. This second part deals with models in Econophysics through the point of view of agent-based modelling. Amongst a large number of multi-agent-based models, we have identified three representative areas. First, using previous work originally presented in the fields of behavioural finance and market microstructure theory, econophysicists have developed agent-based models of order-driven markets that are extensively presented here. Second, kinetic theory models designed to explain some empirical facts on wealth distribution are reviewed. Third, we briefly summarize game theory models by reviewing the now classic minority game and related problems.

This article and the companion paper aim at reviewing recent empirical and theoretical developments usually grouped under the term Econophysics. Since the name was coined in 1995 by merging the words ‘Economics’ and ‘Physics’, this new interdisciplinary field has grown in various directions: theoretical macroeconomics (wealth distribution), microstructure of financial markets (order book modeling), econometrics of financial bubbles and crashes, etc. We discuss the interactions between Physics, Mathematics, Economics and Finance that led to the emergence of Econophysics. We then present empirical studies revealing the statistical properties of financial time series. We begin the presentation with the widely acknowledged ‘stylized facts’, which describe the returns of financial assets—fat tails, volatility clustering, autocorrelation, etc.—and recall that some of these properties are directly linked to the way ‘time’ is taken into account. We continue with the statistical properties observed on order books in financial markets. For the sake of illustrating this review, (nearly) all the stated facts are reproduced using our own high-frequency financial database. Finally, contributions to the study of correlations of assets such as random matrix theory and graph theory are presented. The companion paper will review models in Econophysics from the point of view of agent-based modeling.

We review the basic kinetic wealth-exchange models of Angle [J. Angle, Social Forces 65, 293 (1986); J. Math. Sociol. 26, 217 (2002)], Bennati [E. Bennati, Rivista Internazionale di Scienze Economiche e Commerciali 35, 735 (1988)], Chakraborti and Chakrabarti [A. Chakraborti, B. K. Chakrabarti, Eur. Phys. J. B 17, 167 (2000)], and of Dragulescu and Yakovenko [A. Dragulescu, V.M. Yakovenko, Eur. Phys. J. B 17, 723 (2000)]. Analytical fitting forms for the equilibrium wealth distributions are proposed. The influence of heterogeneity is investigated, the appearance of the fat tail in the wealth distribution and the relaxation to equilibrium are discussed. A unified reformulation of the models considered is suggested.

A mechanism is proposed for the appearance of power-law distributions in various complex systems. It is shown that in a conservative mechanical system composed of subsystems with different numbers of degrees of freedom a robust power-law tail can appear in the equilibrium distribution of energy as a result of certain superpositions of the canonical equilibrium energy densities of the subsystems. The derivation only uses a variational principle based on the Boltzmann entropy, without assumptions outside the framework of canonical equilibrium statistical mechanics. Two examples are discussed, free diffusion on a complex network and a kinetic model of wealth exchange. The mechanism is illustrated in the general case through an exactly solvable mechanical model of a dimensionally heterogeneous system.

Extensive two-dimensional Langevin dynamics simulations are used to determine the effect of steady shear flows on the crystal nucleation kinetics of charge stabilized colloids and colloids whose pair potential possess an attractive shallow well of a few kBT’s attractive colloids . Results show that in both types of systems small amounts of shear speeds up the crystallization process and enhances the quality of the growing crystal signifi- cantly. Moderate shear rates, on the other hand, destroy the ordering in the system. The very high shear rate regime where a reentering transition to the ordered state could exist is not considered in this work. In addition to the crystal nucleation phenomena, the analysis of the transport properties and the characterization of the steady state regime under shear are performed

We present results from a detailed numerical study of the kinetics of phase transformations in a model two-dimensional depletion-driven colloidal system. Transition from a single, dispersed phase to a two-phase coexistence of monomers and clusters is obtained as the depth of the interaction potential among the colloidal particles is changed. Increasing the well depth further, fractal clusters are observed in the simulation. These fractal clusters have a hybrid structure in the sense that they show hexagonal closed-packed crystalline ordering at short length scales and a ramified fractal nature at larger length scales. For sufficiently deep potential wells, the diffusion-limited cluster-cluster aggregation model is recovered in terms of the large-scale fractal dimension Df of the clusters, the kinetic exponent z, and the scaling form of the cluster size distribution. For shallower well depths inside the two-phase coexistence region, simulation results for the kinetics of cluster growth are compared with intermediate-stage phase separation in binary mixtures. In the single-phase region, growth kinetics agree well with a mean-field aggregation-fragmentation model of Sorensen, Zhang, and Taylor.

The dynamical scaling hypothesis for the structure factor, S(q), in depletion-driven colloidal phase separation is studied by carrying out Brownian dynamics simulations. A true dynamical scaling is observed for shallow quenches into the two-phase coexistence region. In such a quench, compact clusters nucleate and grow with time and there is only one characteristic length scale in the system after an initial transient period. Scaling is satisfied beyond this initial period. In contrast, deep quenches lead to fractal cluster growth, and the system is controlled by two characteristic lengths that evolve differently in time [ Huang, Oh and Sorensen Phys. Rev. E 57 875 (1998)]. True dynamical scaling thus cannot be expected to hold. However, an apparent scaling for the structure factor is observed over some period of time when these two characteristic length scales become comparable to each other. We compare our simulation results for the total structure factor to theoretical predictions by HOS by writing it as a product of cluster-cluster and the averaged single-cluster structure factors, each with its own characteristic length.

We present extensive computer simulations of a modified Eden model on a tetragonal lattice. This model is able to reproduce the crossover from mass fractal to surface fractal structures observed experimentally in the clustering process of partially hydrolysed silica particles. © 1996 IOP Publishing Ltd.

Demand outstrips available resources in most situations, which gives rise to competition, interaction and learning. In this article, we review a broad spectrum of multi-agent models of competition (El Farol Bar problem, Minority Game, Kolkata Paise Restaurant problem, Stable marriage problem, Parking space problem and others) and the methods used to understand them analytically. We emphasize the power of concepts and tools from statistical mechanics to understand and explain fully collective phenomena such as phase transitions and long memory, and the mapping between agent heterogeneity and physical disorder. As these methods can be applied to any large-scale model of competitive resource allocation made up of heterogeneous adaptive agent with non-linear interaction, they provide a prospective unifying paradigm for many scientific disciplines.