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In Honor of Professor Serge Galam for His 70th Birthday and Forty Years of Sociophysics

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A special issue of Physics (ISSN 2624-8174). This special issue belongs to the section "Statistical Physics and Nonlinear Phenomena".

Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 13274

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Dr. André Martins

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Guest Editor

Escola de Artes, Ciências e Humanidades, Universidade de São Paulo, São Paulo 05508-220, SP, Brazil
Interests: complex systems; sociophysics; opinion dynamics; evolutionary models; rationality; probabilistic induction

Dr. Taksu Cheon

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Guest Editor

Laboratory of Physics, Kochi University of Technology, Kochi 782-8502, Japan
Interests: quantum mechanics; sociophysics

Prof. Dr. Xijin Tang

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Key Lab on Management, Decision-Making and Information Systems, Institute of Systems Science, Academy of Mathematics and Systems Sciences, Chinese Academy of Sciences, Beijing, China
Interests: meta-synthesis and advanced modeling; social network analysis and knowledge management; opinion mining and opinion dynamics; opinion big data and societal risk perception

Prof. Dr. Bastien Chopard

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Computer Science Department, University of Geneva, 1205 Geneva, Switzerland
Interests: modeling and simulation of complex systems; cellular automata; agent-based modeling; lattice-Boltzmann method; high performance computing

Dr. Soumyajyoti Biswas

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Guest Editor

Department of Physics, SRM University, AP, Andhra Pradesh 522502, India
Interests: statistical mechanics of fracture, earthquake and other disordered systems; agent based models of econophysics and sociophysics

Special Issue Information

Dear Colleagues,

In 1982, Serge Galam and collaborators published five papers that opened the path to a new field of research that they coined Sociophysics. Sociophysics is basically the use of ideas, methods, and theories from physics to describe social systems. However, it is not about metaphors, nor maps, nor narrations.

After a challenging beginning (see Galam’s testimony paper, Physica A 336, 49-55, 2004), Sociophysics today is a flourishing field of research among physicists, mathematicians, and computer scientists. The use of simple behavioral rules, interactions among the simplified agents, complex networks, stochastic models, and other methodologies that are amenable to large computer simulations have already shown a critical capacity to tackle a broad spectrum of social and political issues. The related numerous existing models and approaches developed for complex systems suggest promising outcomes in the near future. Yet, a current challenge in this field is that social systems often lack first principles, conservation properties, and fundamental laws, such as those at the heart of exact sciences.

Current applications of Sociophysics include very diverse topics, from the emergence and spread of extremist opinions and polarization to economic and financial applications, from describing cities to models of crime spread, from modeling terrorism to the spread of radicalism. Those are only examples, and far from a complete list.

Beyond the academic importance of this field, its direct societal impact should not be forgotten. Currently, policymakers face more and more global challenges for which little knowledge is available. Yet, the need for understanding, predicting, and getting prepared for the evolution of our society is crucial. New ideas and investigation methods are much needed. Sociophysics is undoubtedly a vital source of novel insights to tackle those global societal issues.

To celebrate Serge Galam’s 70th birthday and the 40th anniversary of Sociophysics, the journal Physics will hold a Special Issue on Sociophysics and its many applications. As a reminder of the adventuring spirit of the early days of Sociophysics, we are happy to lead this Special Issue in a new emerging young journal. Therefore, we invite the whole community of researchers in this exciting field to contribute to this Special Issue with new and innovative papers.

Dr. André Martins
Dr. Taksu Cheon
Prof. Dr. Xijin Tang
Prof. Dr. Bastien Chopard
Dr. Soumyajyoti Biswas
Guest Editors

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Keywords

sociophysics
social modeling
statistical physics
collective behaviors
disorder
forecasting
universality
complex systems
opinion dynamics
opinion mining
social dynamics networks
modeling and simulation

Published Papers (13 papers)

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Research

16 pages, 1731 KiB

Open AccessArticle

Statistical Mechanics of Social Hierarchies: A Mathematical Model for the Evolution of Human Societal Structures

by Nestor Caticha, Rafael S. Calsaverini and Renato Vicente

Physics 2024, 6(2), 629-644; https://doi.org/10.3390/physics6020041 - 19 Apr 2024

Viewed by 306

Abstract

Social structure may have changed from hierarchical to egalitarian and back along the evolutionary line of humans. Within the tradition of sociophysics, we construct a mathematical model of a society of agents subject to competing cognitive and social navigation constraints and predict, using statistical mechanics methods, that its degree of hierarchy decreases with encephalization and increases with group size, hence suggesting human societies were driven from hierarchical to egalitarian structures by the encephalization during the last few million years and back to hierarchical due to fast demographic changes during the Neolithic. In addition, applied to a different problem, the theory leads to the following predictions for modern pre-literary humans: (i) an intermediate hierarchy degree in mild climates. In harsher climates, societies will be (ii) more egalitarian if organized in small groups (of less than 100 persons) but (iii) more hierarchical if in larger (of more than 1000 persons) groups. The predicted bifurcation, characteristic of a phase transition, is also seen in the empirical cross-cultural record (248 cultures in the Ethnographic Atlas). Full article

(This article belongs to the Special Issue In Honor of Professor Serge Galam for His 70th Birthday and Forty Years of Sociophysics)

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14 pages, 443 KiB

Open AccessArticle

Aging in Some Opinion Formation Models: A Comparative Study

by Jaume Llabrés, Sara Oliver-Bonafoux, Celia Anteneodo and Raúl Toral

Physics 2024, 6(2), 515-528; https://doi.org/10.3390/physics6020034 - 08 Apr 2024

Cited by 1 | Viewed by 238

Abstract

Changes of mind can become less likely the longer an agent has adopted a given opinion state. This resilience or inertia to change has been called “aging”. We perform a comparative study of the effects of aging on the critical behavior of two standard opinion models with pairwise interactions. One of them is the voter model, which is a two-state model with a dynamic that proceeds via social contagion; another is the so-called kinetic exchange model, which allows a third (neutral) state, and its formed opinion depends on the previous opinions of both interacting agents. Furthermore, in the noisy version of both models, random opinion changes are also allowed, regardless of the interactions. Due to aging, the probability of changing diminishes with the age, and to take this into account, we consider algebraic and exponential kernels. We investigate the situation where aging acts only on pairwise interactions. Analytical predictions for the critical curves of the order parameters are obtained for the opinion dynamics on a complete graph, in good agreement with agent-based simulations. For both models considered, the consensus is optimized via an intermediate value of the parameter that rules the rate of decrease of the aging factor. Full article

(This article belongs to the Special Issue In Honor of Professor Serge Galam for His 70th Birthday and Forty Years of Sociophysics)

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15 pages, 344 KiB

Open AccessArticle

A Theory of Best Choice Selection through Objective Arguments Grounded in Linear Response Theory Concepts

by Marcel Ausloos, Giulia Rotundo and Roy Cerqueti

Physics 2024, 6(2), 468-482; https://doi.org/10.3390/physics6020031 - 27 Mar 2024

Viewed by 412

Abstract

In this study, we propose how to use objective arguments grounded in statistical mechanics concepts in order to obtain a single number, obtained after aggregation, which would allow for the ranking of “agents”, “opinions”, etc., all defined in a very broad sense. We aim toward any process which should a priori demand or lead to some consensus in order to attain the presumably best choice among many possibilities. In order to specify the framework, we discuss previous attempts, recalling trivial means of scores—weighted or not—Condorcet paradox, TOPSIS (Technique for Order Preference by Similarity to Ideal Solution), etc. We demonstrate, through geometrical arguments on a toy example and with four criteria, that the pre-selected order of criteria in previous attempts makes a difference in the final result. However, it might be unjustified. Thus, we base our “best choice theory” on the linear response theory in statistical physics: we indicate that one should be calculating correlations functions between all possible choice evaluations, thereby avoiding an arbitrarily ordered set of criteria. We justify the point through an example with six possible criteria. Applications in many fields are suggested. Furthermore, two toy models, serving as practical examples and illustrative arguments are discussed. Full article

(This article belongs to the Special Issue In Honor of Professor Serge Galam for His 70th Birthday and Forty Years of Sociophysics)

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10 pages, 449 KiB

Open AccessArticle

Social Depolarization: Blume–Capel Model

by Miron Kaufman, Sanda Kaufman and Hung T. Diep

Physics 2024, 6(1), 138-147; https://doi.org/10.3390/physics6010010 - 22 Jan 2024

Viewed by 443

Abstract

This study belongs to an emerging area of research seeking ways to depolarize societies in the short run (around events such as elections) as well as in a sustainable fashion. We approach the depolarization process with a model of three homophilic groups (US Democrats, Republicans, and Independents interacting in the context of upcoming federal elections). We expand a previous polarization model, which assumed that each individual interacts with all other individuals in its group with mean-field interactions. We add a depolarization field, which is analogous to the Blume–Capel model’s crystal field. There are currently numerous depolarization efforts around the world, some of which act in ways similar to this depolarization field. We find that for low values of the depolarization field, the system continues to be polarized. When the depolarization field is increased, the polarization decreases. Full article

(This article belongs to the Special Issue In Honor of Professor Serge Galam for His 70th Birthday and Forty Years of Sociophysics)

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15 pages, 679 KiB

Open AccessArticle

Phase Transition in Ant Colony Optimization

by Shintaro Mori, Shogo Nakamura, Kazuaki Nakayama and Masato Hisakado

Physics 2024, 6(1), 123-137; https://doi.org/10.3390/physics6010009 - 18 Jan 2024

Viewed by 429

Abstract

Ant colony optimization (ACO) is a stochastic optimization algorithm inspired by the foraging behavior of ants. We investigate a simplified computational model of ACO, wherein ants sequentially engage in binary decision-making tasks, leaving pheromone trails contingent upon their choices. The quantity of pheromone [...] Read more.

α

, which governs the pheromone levels in the stochastic choice function. In the absence of pheromone evaporation, the system is accurately modeled as a multivariate nonlinear Pólya urn, undergoing phase transition as

α

varies. The probability of selecting the correct answer for each question asymptotically approaches the stable fixed point of the nonlinear Pólya urn. The system exhibits dual stable fixed points for

α \geq α_{c}

and a singular stable fixed point for

α < α_{c}

where

α_{c}

is the critical value. When pheromone evaporates over a time scale

τ

, the phase transition does not occur and leads to a bimodal stationary distribution of probabilities for

α \geq α_{c}

and a monomodal distribution for

α < α_{c}

. Full article

(This article belongs to the Special Issue In Honor of Professor Serge Galam for His 70th Birthday and Forty Years of Sociophysics)

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14 pages, 1482 KiB

Open AccessArticle

Do Successful Researchers Reach the Self-Organized Critical Point?

by Asim Ghosh and Bikas K. Chakrabarti

Physics 2024, 6(1), 46-59; https://doi.org/10.3390/physics6010004 - 30 Dec 2023

Cited by 4 | Viewed by 513

Abstract

The index of success of the researchers is now mostly measured using the Hirsch index (h). Our recent precise demonstration, that statistically

h \sim \sqrt{N_{c}} \sim \sqrt{N_{p}}

, where

N_{p}

and

N_{c}

denote, respectively, the total number [...] Read more.

The index of success of the researchers is now mostly measured using the Hirsch index (h). Our recent precise demonstration, that statistically

h \sim \sqrt{N_{c}} \sim \sqrt{N_{p}}

, where

N_{p}

and

N_{c}

denote, respectively, the total number of publications and total citations for the researcher, suggests that average number of citations per paper (

N_{c} / N_{p}

), and hence h, are statistical numbers (Dunbar numbers) depending on the community or network to which the researcher belongs. We show here, extending our earlier observations, that the indications of success are not reflected by the total citations

N_{c}

, rather by the inequalities among citations from publications to publications. Specifically, we show that for highly successful authors, the yearly variations in the Gini index (g, giving the average inequality of citations for the publications) and the Kolkata index (k, giving the fraction of total citations received by the top

(1 - k)

fraction of publications;

k = 0.80

corresponds to Pareto’s 80/20 law) approach each other to

g = k ≃ 0.82

, signaling a precursor for the arrival of (or departure from) the self-organized critical (SOC) state of his/her publication statistics. Analyzing the citation statistics (from Google Scholar) of thirty successful scientists throughout their recorded publication history, we find that the g and k for the highly successful among them (mostly Nobel laureates, highest rank Stanford cite-scorers, and a few others) reach and hover just above (and then) below that

g = k ≃ 0.82

mark, while for others they remain below that mark. We also find that all the lower (than the SOC mark 0.82) values of k and g fit a linear relationship,

k = 1 / 2 + c g

, with

c = 0.39

, as suggested by an approximate Landau-type expansion of the Lorenz function, and this also indicates

k = g ≃ 0.82

for the (extrapolated) SOC precursor mark. Full article

(This article belongs to the Special Issue In Honor of Professor Serge Galam for His 70th Birthday and Forty Years of Sociophysics)

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15 pages, 2219 KiB

Open AccessArticle

Graph-Based Generalization of Galam Model: Convergence Time and Influential Nodes

by Sining Li and Ahad N. Zehmakan

Physics 2023, 5(4), 1094-1108; https://doi.org/10.3390/physics5040071 - 28 Nov 2023

Viewed by 618

Abstract

We study a graph-based generalization of the Galam opinion formation model. Consider a simple connected graph which represents a social network. Each node in the graph is colored either blue or white, which indicates a positive or negative opinion on a new product or a topic. In each discrete-time round, all nodes are assigned randomly to groups of different sizes, where the node(s) in each group form a clique in the underlying graph. All the nodes simultaneously update their color to the majority color in their group. If there is a tie, each node in the group chooses one of the two colors uniformly at random. Investigating the convergence time of the model, our experiments show that the convergence time is a logarithm function of the number of nodes for a complete graph and a quadratic function for a cycle graph. We also study the various strategies for selecting a set of seed nodes to maximize the final cascade of one of the two colors, motivated by viral marketing. We consider the algorithms where the seed nodes are selected based on the graph structure (nodes’ centrality measures such as degree, betweenness, and closeness) and the individual’s characteristics (activeness and stubbornness). We provide a comparison of such strategies by conducting experiments on different real-world and synthetic networks. Full article

(This article belongs to the Special Issue In Honor of Professor Serge Galam for His 70th Birthday and Forty Years of Sociophysics)

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17 pages, 527 KiB

Open AccessArticle

Phase Diagram for Social Impact Theory in Initially Fully Differentiated Society

by Krzysztof Malarz and Tomasz Masłyk

Physics 2023, 5(4), 1031-1047; https://doi.org/10.3390/physics5040067 - 27 Oct 2023

Cited by 1 | Viewed by 908

Abstract

The study of opinion formation and dynamics is one of the core topics in sociophysics. In this paper, the results of computer simulation of opinion dynamics based on social impact theory are presented. The simulations are based on Latané theory in its computerised version proposed by Nowak, Szamrej and Latané. The active parameters of the model describe the volatility of the actors (social temperature T) and the effective range of interaction (governed by an exponent

α

in a scaling function of distance between actors). Initially, every actor i has his/her own opinion. Our results indicate that ultimately at least 90% of the initial opinions available are removed from the society. For a low social temperature and a long range of interaction, only one opinion survives. Also, a rough sketch of the system phase diagram is presented. It indicates a set of (

α, T

) leading either to (1) the dominance of the unanimity of the opinions or (2) mixtures of unanimity and polarisation, or (3) taking random opinions by actors, or (4) a mixture of the final fates of the systems. The drastic reduction of finally observed opinions vs. their initial variety may be generic for many sociophysical models of opinions formation but masked by assuming an initially small pool of available opinions (in the worst case, in models with only binary opinions). Full article

(This article belongs to the Special Issue In Honor of Professor Serge Galam for His 70th Birthday and Forty Years of Sociophysics)

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16 pages, 979 KiB

Open AccessArticle

Mathematical Programming for the Dynamics of Opinion Diffusion

by Andrea Ellero, Giovanni Fasano and Daniela Favaretto

Physics 2023, 5(3), 936-951; https://doi.org/10.3390/physics5030061 - 11 Sep 2023

Viewed by 1052

Abstract

The focus of this paper is on analyzing the role and the choice of parameters in sociophysics diffusion models by leveraging the potentialities of sociophysics from a mathematical programming perspective. We first present a generalised version of Galam’s opinion diffusion model. For a given selection of the coefficients in our model, this proposal yields the original Galam’s model. The generalised model suggests guidelines for possible alternative selection of its parameters that allow it to foster diffusion. Examples of the parameters selection process as steered by numerical optimisation, taking into account various objectives, are provided. Full article

(This article belongs to the Special Issue In Honor of Professor Serge Galam for His 70th Birthday and Forty Years of Sociophysics)

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12 pages, 557 KiB

Open AccessArticle

Phase Transition in the Galam’s Majority-Rule Model with Information-Mediated Independence

by André L. Oestereich, Marcelo A. Pires, Silvio M. Duarte Queirós and Nuno Crokidakis

Physics 2023, 5(3), 911-922; https://doi.org/10.3390/physics5030059 - 31 Aug 2023

Viewed by 1002

Abstract

We study the Galam’s majority-rule model in the presence of an independent behavior that can be driven intrinsically or can be mediated by information regarding the collective opinion of the whole population. We first apply the mean-field approach where we obtained an explicit time-dependent solution for the order parameter of the model. We complement our results with Monte Carlo simulations where our findings indicate that independent opinion leads to order–disorder continuous nonequilibrium phase transitions. Finite-size scaling analysis show that the model belongs to the mean-field Ising model universality class. Moreover, results from an approach with the Kramers–Moyal coefficients provide insights about the social volatility. Full article

(This article belongs to the Special Issue In Honor of Professor Serge Galam for His 70th Birthday and Forty Years of Sociophysics)

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10 pages, 354 KiB

Open AccessArticle

Opinion Dynamics Systems via Biswas–Chatterjee–Sen Model on Solomon Networks

by Edmundo Alves Filho, Francisco Welington Lima, Tayroni Francisco Alencar Alves, Gladstone de Alencar Alves and Joao Antonio Plascak

Physics 2023, 5(3), 873-882; https://doi.org/10.3390/physics5030056 - 17 Aug 2023

Cited by 1 | Viewed by 880

Abstract

The critical properties of a discrete version of opinion dynamics systems, based on the Biswas–Chatterjee–Sen model defined on Solomon networks with both nearest and random neighbors, are investigated through extensive computer simulations. By employing Monte Carlo algorithms on SNs of different sizes, the magnetic-like variables of the model are computed as a function of the noise parameter. Using the finite-size scaling hypothesis, it is observed that the model undergoes a second-order phase transition. The critical transition noise and the respective ratios of the usual critical exponents are computed in the limit of infinite-size networks. The results strongly indicate that the discrete Biswas–Chatterjee–Sen model is in a different universality class from the other lattices and networks, but in the same universality class as the Ising and majority-vote models on the same Solomon networks. Full article

(This article belongs to the Special Issue In Honor of Professor Serge Galam for His 70th Birthday and Forty Years of Sociophysics)

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11 pages, 2940 KiB

Open AccessArticle

Faculty Hiring Network Reveals Possible Decision-Making Mechanism

by Sunjing Zheng, Nan Jiang, Xiaomeng Li, Mingzhong Xiao and Qinghua Chen

Physics 2023, 5(3), 851-861; https://doi.org/10.3390/physics5030054 - 11 Aug 2023

Viewed by 1188

Abstract

Social physics (or sociophysics) offers new research perspectives for addressing social issues in various domains. In this study, we explore the decision-making process of doctoral graduates during their transition from graduation to employment, drawing on the ideas of sociophysics. We divide the process into two decision steps and propose a generative model based on appropriate assumptions. This model effectively reproduces empirical data, allowing us to derive essential parameters that influence the decision-making process from empirical observations. Through a comparison of the best-fit parameters, we discover that doctoral graduates in business disciplines tend to exhibit more concentrated employment choices, while those in computer science and history disciplines demonstrate a greater diversity of options. Furthermore, we observe that universities consider factors beyond rankings when selecting doctoral graduates. Full article

(This article belongs to the Special Issue In Honor of Professor Serge Galam for His 70th Birthday and Forty Years of Sociophysics)

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20 pages, 781 KiB

Open AccessArticle

Polarization and Consensus in a Voter Model under Time-Fluctuating Influences

by Mauro Mobilia

Physics 2023, 5(2), 517-536; https://doi.org/10.3390/physics5020037 - 08 May 2023

Cited by 5 | Viewed by 2051

Abstract

We study the effect of time-fluctuating social influences on the formation of polarization and consensus in a three-party community consisting of two types of voters (“leftists” and “rightists”) holding extreme opinions, and moderate agents acting as “centrists”. The former are incompatible and do not interact, while centrists hold an intermediate opinion and can interact with extreme voters. When a centrist and a leftist/rightist interact, they can become either both centrists or both leftists/rightists. The population eventually either reaches consensus with one of the three opinions, or a polarization state consisting of a frozen mixture of leftists and rightists. As a main novelty, here agents interact subject to time-fluctuating external influences favouring in turn the spread of leftist and rightist opinions, or the rise of centrism. The fate of the population is determined under various scenarios, and it is shown how the rate of change of external influences can drastically affect the polarization and consensus probabilities, as well as the mean time to reach the final state. Full article

(This article belongs to the Special Issue In Honor of Professor Serge Galam for His 70th Birthday and Forty Years of Sociophysics)

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In Honor of Professor Serge Galam for His 70th Birthday and Forty Years of Sociophysics

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