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Statistical Physics and Social Sciences

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

Deadline for manuscript submissions: closed (31 December 2020) | Viewed by 2299

Special Issue Editors


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Guest Editor
Department of Computer Science, Aalto University School of Science, P.O. Box 15500, 00076 Aalto, Finland
Interests: computational science; data science; complexity of physical, economic, social, and information systems; complex social networks; computational social science; data-driven health science

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Guest Editor
Department of Industrial Engineering and Management, Aalto University School of Science, 00076 Aalto, Finland
Interests: complex systems; network science; sociophysics

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Guest Editor
Aalto University School of Science, FI-00076 AALTO, Finland
Interests: human behavior; complex systems; complex networks; machine learning; data mining

Special Issue Information

Dear Colleagues,

Our societies today as we see them are a result of the interactions continually occurring at the micro as well as macro levels between different actors and entities. The dynamics followed in such interacting systems are a reflection of one of the fundamental characteristics of humans: the social behavior. The current understanding of this complexity and existing theories and models result from a culmination of many different perspectives.

While this subject has been traditionally tackled by the social sciences, there has been a paradigm shift in the last few decades whereby human societies have come to be largely viewed as complex systems, an approach rooted in statistical physics. The description of properties and dynamics of systems with interacting elements and constituents has been the object of study of the latter, with applications in diverse scientific fields. The transdisciplinary exchanges between statistical physics and social sciences, armed with the availability of large digital datasets and computing power, have helped to establish several new and active research agendas and methodologies, such as econophysics, network science, sociophysics, and science of cities, to name a few. This is, overall, a broad endeavour to connect human behavior observed at the individual level with the structure and function of societies at the population level.

Novel contributions related to the afore-mentioned areas, from any researcher studying social phenomena from the perspective of the statistical physics, are welcome in this Special Issue, which covers a variety of social science-related fields, including the following suggested topics:

  • Collective phenomena in techno-social and socio-economical systems;
  • Social human behavior, self-organizing social processes;
  • Social networks and modelling;
  • Human mobility, urban growth, and community-formation processes;
  • Spreading processes of information and epidemics;
  • Econophysics, game theory;
  • Social signal processing, information-theoretic concepts for human behavior;
  • Entropy-based measures for digital footprints;
  • Social media analysis and models;
  • Agent-based modelling.

Prof. Kimmo Kaski
Dr. Kunal Bhattacharya
Dr. Daniel Monsivais-Velazquez
Guest Editors

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

  • Entropy
  • Information theory
  • Self-organization
  • Statistical mechanics
  • Complex networks
  • Complex systems
  • Social network analysis
  • Machine learning
  • Artificial intelligence
  • Human behavior
  • Mobility
  • Science of cities
  • Multiagent systems
  • Homophily

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Published Papers (1 paper)

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Research

13 pages, 1546 KiB  
Article
Effect of Savings on a Gas-Like Model Economy with Credit and Debt
by Guillermo Chacón-Acosta and Vanessa Ángeles-Sánchez
Entropy 2021, 23(2), 196; https://doi.org/10.3390/e23020196 - 5 Feb 2021
Cited by 1 | Viewed by 1720
Abstract
In kinetic exchange models, agents make transactions based on well-established microscopic rules that give rise to macroscopic variables in analogy to statistical physics. These models have been applied to study processes such as income and wealth distribution, economic inequality sources, economic growth, etc., [...] Read more.
In kinetic exchange models, agents make transactions based on well-established microscopic rules that give rise to macroscopic variables in analogy to statistical physics. These models have been applied to study processes such as income and wealth distribution, economic inequality sources, economic growth, etc., recovering well-known concepts in the economic literature. In this work, we apply ensemble formalism to a geometric agents model to study the effect of saving propensity in a system with money, credit, and debt. We calculate the partition function to obtain the total money of the system, with which we give an interpretation of the economic temperature in terms of the different payment methods available to the agents. We observe an interplay between the fraction of money that agents can save and their maximum debt. The system’s entropy increases as a function of the saved proportion, and increases even more when there is debt. Full article
(This article belongs to the Special Issue Statistical Physics and Social Sciences)
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