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Dynamics in Biological and Social Networks
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Dynamics in Biological and Social Networks

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

Deadline for manuscript submissions: 20 November 2025 | Viewed by 6775

Special Issue Editor

Dr. Luiz Henrique Alves Monteiro

E-Mail Website1 Website2
Guest Editor
1. Escola de Engenharia, Universidade Presbiteriana Mackenzie, São Paulo 01302-907, Brazil
2. Escola Politécnica, Universidade de São Paulo, São Paulo 05508-010, Brazil
Interests: complex networks; dynamical systems; epidemiology; game theory; social networks; synchronization

Special Issue Information

Dear Colleagues,

The dynamics of biological and social systems result from the intricate interaction of many elements; hence, such systems are usually represented by complex networks. In fact, life depends on the activity of genes, neurons, proteins; ecosystems rely on their biodiversity; societies are affected by the spread of diseases, information, opposing ideas. From an academic perspective, these subjects are translated into investigations on a wide range of topics, such as:

  • Chaotic behavior;
  • Epidemiology;
  • Gene regulatory networks;
  • Information flow;
  • Metabolic pathways;
  • Neuronal networks;
  • Online social media;
  • Opinion dynamics;
  • Population dynamics;
  • Protein–protein interaction;
  • Social network mining;
  • Synchronization.

These investigations are based, for instance, on cellular automata, differential equations, game-theoretic models, multi-agent simulations, network analysis. Thus, analytical and numerical techniques are employed to deepen our understanding of real-world phenomena.

Entropy measures have been proposed to quantify the amount of variability and the level of complexity found in a broad spectrum of networks. This Special Issue of Entropy is devoted to studies on the dynamics in biological and social networks. These studies should be carried out, at least partially, drawing upon concepts from information theory. Submissions of original contributions and review articles are both welcome. The submitted manuscripts will be peer-reviewed and the authors will receive timely feedback. The deadline for manuscript submission is 31 August 2024.

Dr. Luiz Henrique Alves Monteiro
Guest Editor

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

  • agent-based model
  • cellular automata
  • complex network
  • dynamical systems
  • entropy measures
  • game theory
  • social media
  • social network
  • systems biology

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (4 papers)

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Research

31 pages, 632 KiB  
Article
Advancing Mathematical Epidemiology and Chemical Reaction Network Theory via Synergies Between Them
by Florin Avram, Rim Adenane and Mircea Neagu
Entropy 2024, 26(11), 936; https://doi.org/10.3390/e26110936 - 31 Oct 2024
Viewed by 1195
Abstract
Our paper reviews some key concepts in chemical reaction network theory and mathematical epidemiology, and examines their intersection, with three goals. The first is to make the case that mathematical epidemiology (ME), and also related sciences like population dynamics, virology, ecology, etc., could [...] Read more.
Our paper reviews some key concepts in chemical reaction network theory and mathematical epidemiology, and examines their intersection, with three goals. The first is to make the case that mathematical epidemiology (ME), and also related sciences like population dynamics, virology, ecology, etc., could benefit by adopting the universal language of essentially non-negative kinetic systems as developed by chemical reaction network (CRN) researchers. In this direction, our investigation of the relations between CRN and ME lead us to propose for the first time a definition of ME models, stated in Open Problem 1. Our second goal is to inform researchers outside ME of the convenient next generation matrix (NGM) approach for studying the stability of boundary points, which do not seem sufficiently well known. Last but not least, we want to help students and researchers who know nothing about either ME or CRN to learn them quickly, by offering them a Mathematica package “bootcamp”, including illustrating notebooks (and certain sections below will contain associated suggested notebooks; however, readers with experience may safely skip the bootcamp). We hope that the files indicated in the titles of various sections will be helpful, though of course improvement is always possible, and we ask the help of the readers for that. Full article
(This article belongs to the Special Issue Dynamics in Biological and Social Networks)
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21 pages, 4421 KiB  
Article
Three-Stage Cascade Information Attenuation for Opinion Dynamics in Social Networks
by Haomin Wang, Youyuan Li and Jia Chen
Entropy 2024, 26(10), 851; https://doi.org/10.3390/e26100851 - 8 Oct 2024
Viewed by 1057
Abstract
In social network analysis, entropy quantifies the uncertainty or diversity of opinions, reflecting the complexity of opinion dynamics. To enhance the understanding of how opinions evolve, this study introduces a novel approach to modeling opinion dynamics in social networks by incorporating three-stage cascade [...] Read more.
In social network analysis, entropy quantifies the uncertainty or diversity of opinions, reflecting the complexity of opinion dynamics. To enhance the understanding of how opinions evolve, this study introduces a novel approach to modeling opinion dynamics in social networks by incorporating three-stage cascade information attenuation. Traditional models have often neglected the influence of second- and third-order neighbors and the attenuation of information as it propagates through a network. To correct this oversight, we redefine the interaction weights between individuals, taking into account the distance of opining, bounded confidence, and information attenuation. We propose two models of opinion dynamics using a three-stage cascade mechanism for information transmission, designed for environments with either a single or two subgroups of opinion leaders. These models capture the shifts in opinion distribution and entropy as information propagates and attenuates through the network. Through simulation experiments, we examine the ingredients influencing opinion dynamics. The results demonstrate that an increased presence of opinion leaders, coupled with a higher level of trust from their followers, significantly amplifies their influence. Furthermore, comparative experiments highlight the advantages of our proposed models, including rapid convergence, effective leadership influence, and robustness across different network structures. Full article
(This article belongs to the Special Issue Dynamics in Biological and Social Networks)
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16 pages, 1081 KiB  
Article
Optimizing Contact Network Topological Parameters of Urban Populations Using the Genetic Algorithm
by Abimael R. Sergio and Pedro H. T. Schimit
Entropy 2024, 26(8), 661; https://doi.org/10.3390/e26080661 - 3 Aug 2024
Cited by 1 | Viewed by 2051
Abstract
This paper explores the application of complex network models and genetic algorithms in epidemiological modeling. By considering the small-world and Barabási–Albert network models, we aim to replicate the dynamics of disease spread in urban environments. This study emphasizes the importance of accurately mapping [...] Read more.
This paper explores the application of complex network models and genetic algorithms in epidemiological modeling. By considering the small-world and Barabási–Albert network models, we aim to replicate the dynamics of disease spread in urban environments. This study emphasizes the importance of accurately mapping individual contacts and social networks to forecast disease progression. Using a genetic algorithm, we estimate the input parameters for network construction, thereby simulating disease transmission within these networks. Our results demonstrate the networks’ resemblance to real social interactions, highlighting their potential in predicting disease spread. This study underscores the significance of complex network models and genetic algorithms in understanding and managing public health crises. Full article
(This article belongs to the Special Issue Dynamics in Biological and Social Networks)
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15 pages, 468 KiB  
Article
On Playing with Emotion: A Spatial Evolutionary Variation of the Ultimatum Game
by D. Y. Charcon and L. H. A. Monteiro
Entropy 2024, 26(3), 204; https://doi.org/10.3390/e26030204 - 27 Feb 2024
Viewed by 1651
Abstract
The Ultimatum Game is a simplistic representation of bargaining processes occurring in social networks. In the standard version of this game, the first player, called the proposer, makes an offer on how to split a certain amount of money. If the second player, [...] Read more.
The Ultimatum Game is a simplistic representation of bargaining processes occurring in social networks. In the standard version of this game, the first player, called the proposer, makes an offer on how to split a certain amount of money. If the second player, called the responder, accepts the offer, the money is divided according to the proposal; if the responder declines the offer, both players receive no money. In this article, an agent-based model is employed to evaluate the performance of five distinct strategies of playing a modified version of this game. A strategy corresponds to instructions on how a player must act as the proposer and as the responder. Here, the strategies are inspired by the following basic emotions: anger, fear, joy, sadness, and surprise. Thus, in the game, each interacting agent is a player endowed with one of these five basic emotions. In the modified version explored in this article, the spatial dimension is taken into account and the survival of the players depends on successful negotiations. Numerical simulations are performed in order to determine which basic emotion dominates the population in terms of prevalence and accumulated money. Information entropy is also computed to assess the time evolution of population diversity and money distribution. From the obtained results, a conjecture on the emergence of the sense of fairness is formulated. Full article
(This article belongs to the Special Issue Dynamics in Biological and Social Networks)
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