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Computational and Statistical Physics Approaches for Complex Systems and Social Phenomena

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A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Statistical Physics".

Deadline for manuscript submissions: closed (29 February 2020) | Viewed by 18308

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Prof. Dr. Hung T. Diep

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Guest Editor

Laboratoire de Physique Théorique et Modélisation Université de Cergy-Pontoise, CNRS, UMR 8089 2, avenue Adolphe Chauvin, CEDEX, 95302 Cergy-Pontoise, France
Interests: theoretical physics with focus on critical phenomena and phase transitions
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Dear colleagues,

Since the 80s, methods in statistical physics have been used in various domains other than physics such as biology and neuroscience. They are also used nowadays in social sciences such as politics, economics, and sociology [1-5]. Computational methods, which have been widely developed in physics and mathematics thanks to the extremely rapid increase of computer capacity, contribute a great deal to the study of properties of the so-called complex systems [4-6]. Complex systems do not mean only systems with complicated interactions in physics; they also mean current interdisciplinary systems involving different components in scales and nature with poorly defined mutual interactions. The word “complex systems” is used as a broad term to describe problems that need interdisciplinary approaches. They include climate systems, the human brain, social conflicts, and economic issues. These interdisciplinary approaches are borrowed from statistical physics, information theory, nonlinear dynamics, sociology, economics, and biology. Novel phenomena such as self-organized entities, adaptation, feedback loops, spontaneous order, emergence, and nonlinearity are a few striking features.

This Special Issue focuses on investigations of complex systems using methods from statistical physics and computer simulations. Statistical physics is found to be a very efficient tool to study the behavior of human individuals in society, provided appropriate interactions between them are different from those between particles [see for example discussions in Ref. 4 and 5]. In addition, the interpretation of physical parameters in terms of human behavior is also a challenge for the time to come.

We invite contributions to this Special Issue from researchers who study complex systems with the use of statistical physics and computational methods such as Monte Carlo simulation. Contributions may be original papers or reviews.

Prof. Dr. Hung T. Diep
Guest Editor

References

Galam, S. Sociophysics: A Physicist’s Modeling of Psycho-Political Phenomena; Springer Science & Business Media: New York, NY, USA, 2012.
Barnes, T.J.; Wilson, M.W. Big data, social physics, and spatial analysis: The early years. Big Data Soc. 2014, 1–14.
Schweitzer, F. Sociophysics. Phys. Today 2018, 71, 40.
Diep, H.T.; Kaufman, M.; Kaufman, S. Dynamics of Two-Group Conflicts: A Statistical Model. Phys. A Stat. Mech. Appl. 2017, 469, 183–199.
Kaufman, M.; Diep, H.T.; Kaufman, S. Sociophysics of Intractable Conflicts: Three-Group Dynamics. Phys. A Stat. Mech. Appl. 2019, 517, 175–187.
Stauffer, D. Sociophysics simulations. Comput. Sci. Eng. 2003, 5, 71–75.

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Entropy is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

Statistical physics approaches for complex system Computer simulations for complex systems
Computational methods for social sciences
Sociophysics
Nonlinearity and synchronization in complex systems
Self-organized systems
Complex systems in politics, economics, environment

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Published Papers (6 papers)

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Research

12 pages, 2167 KiB

Open AccessArticle

Sociophysics Analysis of Multi-Group Conflicts

by Miron Kaufman, Hung T. Diep and Sanda Kaufman

Entropy 2020, 22(2), 214; https://doi.org/10.3390/e22020214 - 14 Feb 2020

Cited by 6 | Viewed by 2324

Abstract

We present our research on the application of statistical physics techniques to multi-group social conflicts. We identify real conflict situations of which the characteristics correspond to the model. We offer realistic assumptions about conflict behaviors that get factored into model-generated scenarios. The scenarios can inform conflict research and strategies for conflict management. We discuss model applications to two- and three-group conflicts. We identify chaotic time evolution of mean attitudes and the occurrence of strange attractors. We examine the role that the range of interactions plays with respect to the occurrence of chaotic behavior. Full article

(This article belongs to the Special Issue Computational and Statistical Physics Approaches for Complex Systems and Social Phenomena)

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15 pages, 4328 KiB

Open AccessArticle

Co-Evolution of Complex Network Public Goods Game under the Edges Rules

by Xingping Sun, Yibing Li, Hongwei Kang, Yong Shen, Jian Peng, Haoyu Wang and Qingyi Chen

Entropy 2020, 22(2), 199; https://doi.org/10.3390/e22020199 - 08 Feb 2020

Cited by 6 | Viewed by 2627

Abstract

The reconnection of broken edges is an effective way to avoid drawback for the commons in past studies. Inspired by this, we proposed a public goods game model under the edges rules, where we evaluate the weight of edges by their nodes’ payoff. The results proved that the game obtains a larger range of cooperation with a small gain factor by this proposed model by consulting Monte Carlo simulations (MCS) and real experiments. Furthermore, as the following the course of game and discussing the reason of cooperation, in the research, we found that the distribution entropy of the excess average degree is able to embody and predict the presence of cooperation. Full article

(This article belongs to the Special Issue Computational and Statistical Physics Approaches for Complex Systems and Social Phenomena)

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19 pages, 1342 KiB

Open AccessArticle

Asymmetric Contrarians in Opinion Dynamics

by Serge Galam and Taksu Cheon

Entropy 2020, 22(1), 25; https://doi.org/10.3390/e22010025 - 24 Dec 2019

Cited by 8 | Viewed by 2808

Abstract

Asymmetry in contrarian behavior is investigated within the Galam model of opinion dynamics using update groups of size 3 with two competing opinions A and B. Denoting x and y the respective proportions of A and B contrarians, four schemes of implementations are studied. The first scheme activates contrarians after each series of updates with probabilities x and y for agents holding respectively opinion A and B. Second scheme activates contrarians within the update groups only against global majority with probability x when A is the majority and y when B is the majority. The third scheme considers in-group contrarians acting prior to the local majority update against both local majority and minority opinions. The last scheme activates in-group contrarians prior to the local majority update but only against the local majority. The main result is the loss of the fifty–fifty attractor produced by symmetric contrarians. Producing a bit less contrarians on its own side than the other side becomes the key to win a public debate, which in turn can guarantee an election victory. The associated phase diagram of opinion dynamics is found to exhibit a rich variety of counterintuitive results. Full article

(This article belongs to the Special Issue Computational and Statistical Physics Approaches for Complex Systems and Social Phenomena)

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19 pages, 3855 KiB

Open AccessArticle

Modeling the Disorder of Closed System by Multi-Agent Based Simulation

by Krzysztof Małecki, Tomasz M. Gwizdałła and Paweł Bieńko

Entropy 2019, 21(11), 1105; https://doi.org/10.3390/e21111105 - 12 Nov 2019

Cited by 2 | Viewed by 2657

Abstract

Mess (disorder)—there are many different meanings related to this problem. The explicit majority comes from the area of philosophical, social and medical sciences. In our paper, we try to present the engineering aspect of the concept of disorder. We propose a mathematical model which describes the effects and consequences concerning the process of making the mess. We use Multi-Agent Modeling, where there are several independent agents with decision-making ability. Each agent has the ability to communicate and perceive for achieving its own aim. We use square grid n × n with objects which can be moved by agents to another places. The degree of disorder of the system is examined by the value of entropy. Using computer simulation, we investigate the time needed to find the desired thing in an environment in which agents (in real life, people) co-exist and they have different tendencies to tidiness. The cost of mess is counted as the number of attempts to access the object in the analyzed system and the time needed to locate the object. Full article

(This article belongs to the Special Issue Computational and Statistical Physics Approaches for Complex Systems and Social Phenomena)

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15 pages, 318 KiB

Open AccessArticle

How Network Topologies Impact Project Alliance Performance: Evidence from the Movie Industry

by Xin-Jie Zhang, Yong Tang, Jason Xiong, Wei-Jia Wang and Yi-Cheng Zhang

Entropy 2019, 21(9), 859; https://doi.org/10.3390/e21090859 - 03 Sep 2019

Cited by 9 | Viewed by 3048

Abstract

In many industries, partners are interconnected in project alliances that have limited lifespans and clearly-defined boundaries. The transparency of the movie industry provides a unique opportunity to study how alliance network topologies impact the performance of project alliances from the perspectives of social networks and organization theories. In this work, we compiled a massive movie dataset and constructed alliance networks for both movie production and distribution companies. Using the box office as the proxy for the financial performance of a movie project alliance, this research investigates how the two alliance networks impact the box office. We introduce the social network properties of degrees, centralities, and structural holes as alliance network variables into empirical regression models. The results show that alliance networks have a significant influence on the box office. The degrees of production companies and the structural holes of distribution companies are especially important to achieve success in the box office. The results add new evidence for the study of the movie economy and alliance networks. Meanwhile, this work also provides implications for the movie industry by revealing that it is essential to wisely choose partners that are appropriately embedded in alliance networks for the success of a movie project. Full article

(This article belongs to the Special Issue Computational and Statistical Physics Approaches for Complex Systems and Social Phenomena)

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18 pages, 771 KiB

Open AccessEditor’s ChoiceArticle

Is Independence Necessary for a Discontinuous Phase Transition within the q-Voter Model?

by Angelika Abramiuk, Jakub Pawłowski and Katarzyna Sznajd-Weron

Entropy 2019, 21(5), 521; https://doi.org/10.3390/e21050521 - 23 May 2019

Cited by 16 | Viewed by 4037

Abstract

We ask a question about the possibility of a discontinuous phase transition and the related social hysteresis within the q-voter model with anticonformity. Previously, it was claimed that within the q-voter model the social hysteresis can emerge only because of an independent behavior, and for the model with anticonformity only continuous phase transitions are possible. However, this claim was derived from the model, in which the size of the influence group needed for the conformity was the same as the size of the group needed for the anticonformity. Here, we abandon this assumption on the equality of two types of social response and introduce the generalized model, in which the size of the influence group needed for the conformity

q_{c}

and the size of the influence group needed for the anticonformity

q_{a}

are independent variables and in general

q_{c} \neq q_{a}

. We investigate the model on the complete graph, similarly as it was done for the original q-voter model with anticonformity, and we show that such a generalized model displays both types of phase transitions depending on parameters

q_{c}

and

q_{a}

. Full article

(This article belongs to the Special Issue Computational and Statistical Physics Approaches for Complex Systems and Social Phenomena)

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