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Structure and Dynamics of Complex Socioeconomic Networks
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Structure and Dynamics of Complex Socioeconomic Networks

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

Deadline for manuscript submissions: closed (15 December 2021) | Viewed by 32614

Special Issue Editors

Prof. Dr. Wei-Xing Zhou

E-Mail Website
Guest Editor
School of Business and Department of Mathematics, East China University of Science and Technology, Shanghai 200237, China
Interests: econophysics; sociophysics; complex economic networks; complex financial networks; fractal analysis; agent-based modelling; international trade networks
Prof. Dr. Zhi-Qiang Jiang

E-Mail Website
Guest Editor
School of Business, East China University of Science and Technology, Shanghai 200237, China
Interests: econophysics; sociophysics; complex economic networks; complex financial networks; fractal analysis; cooperation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleague,

Complex systems are ubiquitous in nature and human society, and are composed of microscopic units with nonlinear interactions that can be presented as complex networks. In the past decades, with the development of information technology, huge datasets have become available in diverse fields of social and economic activities, and the research on complex socioeconomic networks has flourished, significantly deepening our understanding of socioeconomic behaviors.

The behavior of a complex socioeconomic system is mainly determined by the structure and dynamics of the underlying network. From the viewpoint of econophysics and sociophysics, there is still huge room to investigate complex socioeconomic networks to develop new models and unveil novel or distinct properties, such as the measure, contagion, early warning, and containment of systemic social and economic risks.

This Special Issue aims at collecting theoretical, empirical, computational, and experimental contributions related to complex socioeconomic networks from all fields. Applications of complexity and entropy are particularly welcome. All submissions should concentrate on the structure or dynamics of complex socioeconomic networks. Comprehensive reviews are also welcome.

Prof. Dr. Wei-Xing Zhou
Prof. Dr. Zhi-Qiang Jiang
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

  • complex social networks
  • complex economic networks
  • complex financial networks
  • complexity and entropy
  • structure and dynamics
  • network robustness
  • systemic risks
  • network vulnerability
  • network modeling

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Published Papers (10 papers)

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Research

16 pages, 7701 KiB  
Article
Analysis of the Structure and Dynamics of European Flight Networks
by Matteo Milazzo, Federico Musciotto, Salvatore Miccichè and Rosario N. Mantegna
Entropy 2022, 24(2), 248; https://doi.org/10.3390/e24020248 - 8 Feb 2022
Cited by 6 | Viewed by 2662
Abstract
We analyze structure and dynamics of flight networks of 50 airlines active in the European airspace in 2017. Our analysis shows that the concentration of the degree of nodes of different flight networks of airlines is markedly heterogeneous among airlines reflecting heterogeneity of [...] Read more.
We analyze structure and dynamics of flight networks of 50 airlines active in the European airspace in 2017. Our analysis shows that the concentration of the degree of nodes of different flight networks of airlines is markedly heterogeneous among airlines reflecting heterogeneity of the airline business models. We obtain an unsupervised classification of airlines by performing a hierarchical clustering that uses a correlation coefficient computed between the average occurrence profiles of 4-motifs of airline networks as similarity measure. The hierarchical tree is highly informative with respect to properties of the different airlines (for example, the number of main hubs, airline participation to intercontinental flights, regional coverage, nature of commercial, cargo, leisure or rental airline). The 4-motif patterns are therefore distinctive of each airline and reflect information about the main determinants of different airlines. This information is different from what can be found looking at the overlap of directed links. Full article
(This article belongs to the Special Issue Structure and Dynamics of Complex Socioeconomic Networks)
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9 pages, 7595 KiB  
Article
Enhancement of Cooperation and Reentrant Phase of Prisoner’s Dilemma Game on Signed Networks
by Jae Han Choi, Sungmin Lee and Jae Woo Lee
Entropy 2022, 24(2), 144; https://doi.org/10.3390/e24020144 - 18 Jan 2022
Cited by 2 | Viewed by 1880
Abstract
We studied the prisoner’s dilemma game as applied to signed networks. In signed networks, there are two types of links: positive and negative. To establish a payoff matrix between players connected with a negative link, we multiplied the payoff matrix between players connected [...] Read more.
We studied the prisoner’s dilemma game as applied to signed networks. In signed networks, there are two types of links: positive and negative. To establish a payoff matrix between players connected with a negative link, we multiplied the payoff matrix between players connected with a positive link by −1. To investigate the effect of negative links on cooperating behavior, we performed simulations for different negative link densities. When the negative link density is low, the density of the cooperator becomes zero because there is an increasing temptation payoff, b. Here, parameter b is the payoff received by the defector from playing the game with a cooperator. Conversely, when the negative link density is high, the cooperator density becomes almost 1 as b increases. This is because players with a negative link will suffer more payoff damage if they do not cooperate with each other. The negative link forces players to cooperate, so cooperating behavior is enhanced. Full article
(This article belongs to the Special Issue Structure and Dynamics of Complex Socioeconomic Networks)
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10 pages, 430 KiB  
Article
Quantifying the Endogeneity in Online Donations
by Peng Wang, Jinyi Li, Yinjie Ma and Zhiqiang Jiang
Entropy 2021, 23(12), 1667; https://doi.org/10.3390/e23121667 - 11 Dec 2021
Cited by 2 | Viewed by 2771
Abstract
Charitable crowdfunding provides a new channel for people and families suffering from unforeseen events, such as accidents, severe illness, and so on, to seek help from the public. Thus, finding the key determinants which drive the fundraising process of crowdfunding campaigns is of [...] Read more.
Charitable crowdfunding provides a new channel for people and families suffering from unforeseen events, such as accidents, severe illness, and so on, to seek help from the public. Thus, finding the key determinants which drive the fundraising process of crowdfunding campaigns is of great importance, especially for those suffering. With a unique data set containing 210,907 crowdfunding projects covering a period from October 2015 to June 2020, from a famous charitable crowdfunding platform, specifically Qingsong Chou, we will reveal how many online donations are due to endogeneity, referring to the positive feedback process of attracting more people to donate through broadcasting campaigns in social networks by donors. For this aim, we calibrate three different Hawkes processes to the event data of online donations for each crowdfunding campaign on each day, which allows us to estimate the branching ratio, a measure of endogeneity. It is found that the online fundraising process works in a sub-critical state and nearly 70–90% of the online donations are endogenous. Furthermore, even though the fundraising amount, number of donations, and number of donors decrease rapidly after the crowdfunding project is created, the measure of endogeneity remains stable during the entire lifetime of crowdfunding projects. Our results not only deepen our understanding of online fundraising dynamics but also provide a quantitative framework to disentangle the endogenous and exogenous dynamics in complex systems. Full article
(This article belongs to the Special Issue Structure and Dynamics of Complex Socioeconomic Networks)
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23 pages, 1996 KiB  
Article
Crash Diagnosis and Price Rebound Prediction in NYSE Composite Index Based on Visibility Graph and Time-Evolving Stock Correlation Network
by Yuxuan Xiu, Guanying Wang and Wai Kin Victor Chan
Entropy 2021, 23(12), 1612; https://doi.org/10.3390/e23121612 - 30 Nov 2021
Cited by 9 | Viewed by 4923
Abstract
This study proposes a framework to diagnose stock market crashes and predict the subsequent price rebounds. Based on the observation of anomalous changes in stock correlation networks during market crashes, we extend the log-periodic power-law model with a metric that is proposed to [...] Read more.
This study proposes a framework to diagnose stock market crashes and predict the subsequent price rebounds. Based on the observation of anomalous changes in stock correlation networks during market crashes, we extend the log-periodic power-law model with a metric that is proposed to measure network anomalies. To calculate this metric, we design a prediction-guided anomaly detection algorithm based on the extreme value theory. Finally, we proposed a hybrid indicator to predict price rebounds of the stock index by combining the network anomaly metric and the visibility graph-based log-periodic power-law model. Experiments are conducted based on the New York Stock Exchange Composite Index from 4 January 1991 to 7 May 2021. It is shown that our proposed method outperforms the benchmark log-periodic power-law model on detecting the 12 major crashes and predicting the subsequent price rebounds by reducing the false alarm rate. This study sheds light on combining stock network analysis and financial time series modeling and highlights that anomalous changes of a stock network can be important criteria for detecting crashes and predicting recoveries of the stock market. Full article
(This article belongs to the Special Issue Structure and Dynamics of Complex Socioeconomic Networks)
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16 pages, 2190 KiB  
Article
Spatial Correlation Network and Regional Differences for the Development of Digital Economy in China
by Luyang Tang, Bangke Lu and Tianhai Tian
Entropy 2021, 23(12), 1575; https://doi.org/10.3390/e23121575 - 25 Nov 2021
Cited by 52 | Viewed by 4585
Abstract
The rapid development of the digital economy is a powerful driving force to promote high-quality economic growth all over the world. Although a number of studies have been conducted to investigate the development of the digital economy in China, these studies pay little [...] Read more.
The rapid development of the digital economy is a powerful driving force to promote high-quality economic growth all over the world. Although a number of studies have been conducted to investigate the development of the digital economy in China, these studies pay little attention to the spatial linkages between the 30 provinces in China and the developmental differences between northern and southern China. Using Chinese digital economic data from 2004 to 2019, we propose an index system to measure the developmental levels of the digital economy and obtain the annual developmental levels of these provinces by using the factor analysis method. We analyze the regional differences of developmental levels by using the Theil index and kernel density estimation method. More importantly, the network method is used to analyze the correlations between the developmental levels of the digital economy in all provinces of China. By decomposing regional differences, our study shows that polarized and uncoordinated development is prominent. The development level of the digital economy in the southern region is higher than that in the northern region. In terms of regional correlations, the network study suggests that there are beneficial and spillover effects of the digital economy development between provinces. Based on the analysis results, we propose policies for improving the development of the digital economy in China. Full article
(This article belongs to the Special Issue Structure and Dynamics of Complex Socioeconomic Networks)
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19 pages, 999 KiB  
Article
Testing the Social Bubble Hypothesis on the Early Dynamics of a Scientific Project: The FET Flagship Candidate FuturICT (2010–2013)
by Monika Gisler and Didier Sornette
Entropy 2021, 23(10), 1279; https://doi.org/10.3390/e23101279 - 29 Sep 2021
Cited by 2 | Viewed by 3329
Abstract
We present an analysis of a large emerging scientific project in the light provided by the social bubbles hypothesis (SBH) that we have introduced in earlier papers. The SBH claims that, during an innovation boom or technological revolution, strong social interactions between enthusiastic [...] Read more.
We present an analysis of a large emerging scientific project in the light provided by the social bubbles hypothesis (SBH) that we have introduced in earlier papers. The SBH claims that, during an innovation boom or technological revolution, strong social interactions between enthusiastic supporters weave a network of reinforcing feedbacks that leads to widespread endorsement and extraordinary commitment, beyond what would be rationalized by a standard cost–benefit analysis. By probing the (Future and Emerging Technologies) FET Flagship candidate FuturICT project, as it developed in 2010–2013, we aimed at better understanding how a favorable climate was engineered, allowing the dynamics and risk-taking behaviors to evolve. We document that significant risk-taking was indeed clearly found—especially during workshops and meetings, for instance, in the form of the time allocation of participants, who seemed not to mind their precious time being given to the project and who exhibited many signs of enthusiasm. In this sense, the FuturICT project qualifies as a social bubble in the making when considered at the group level. In contrast, risk-perception at the individual level remained high and not everyone involved shared the exuberance cultivated by the promoters of FuturICT. As a consequence, those not unified under the umbrella of the core vision built niches for themselves that were stimulating enough to stay with the project, but not on a basis of blind over-optimism. Our detailed field study shows that, when considering individuals in isolation, the characteristics associated with a social bubble can vary significantly in the presence of other factors besides exaggerated risk-taking. Full article
(This article belongs to the Special Issue Structure and Dynamics of Complex Socioeconomic Networks)
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18 pages, 1883 KiB  
Article
Network-Based Driving Force of National Economic Development: A Social Capital Perspective
by Lizhi Xing, Xi Ai, Jiaqi Ren and Dawei Wang
Entropy 2021, 23(10), 1276; https://doi.org/10.3390/e23101276 - 29 Sep 2021
Cited by 4 | Viewed by 2272
Abstract
Network science has been widely applied in theoretical and empirical studies of global value chain (GVC), and many related articles have emerged, forming many more mature and complete analytical frameworks. Among them, the GVC accounting method based on complex network theory is different [...] Read more.
Network science has been widely applied in theoretical and empirical studies of global value chain (GVC), and many related articles have emerged, forming many more mature and complete analytical frameworks. Among them, the GVC accounting method based on complex network theory is different from the mainstream economics in both research angle and content. In this paper, we build up global industrial value chain network (GIVCN) models based on World Input–Output Database, introduce the theoretical framework of Social Capital, and define the network-based indicators with economic meanings. Second, we follow the econometric framework to analyze the hypothesis and test whether it is true. Finally, we study how the three types of capital constituted by these indicators interact with each other, and discuss their impact on the social capital (economic development level, i.e., GDP). The results prove that the structural capital (industrial status) has a positive impact on the social capital; the relational capital (industrial correlation) has a positive impact on both social capital and structural capital; the cognitive capital (industrial structure) has a small impact on the social capital, structural capital, and relational capital. Full article
(This article belongs to the Special Issue Structure and Dynamics of Complex Socioeconomic Networks)
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15 pages, 8138 KiB  
Article
Microstructural Characteristics of the Weighted and Directed International Crop Trade Networks
by Yin-Ting Zhang and Wei-Xing Zhou
Entropy 2021, 23(10), 1250; https://doi.org/10.3390/e23101250 - 26 Sep 2021
Cited by 11 | Viewed by 2481
Abstract
With increasing global demand for food, international food trade is playing a critical role in balancing the food supply and demand across different regions. Here, using trade datasets of four crops that provide more than 50% of the calories consumed globally, we constructed [...] Read more.
With increasing global demand for food, international food trade is playing a critical role in balancing the food supply and demand across different regions. Here, using trade datasets of four crops that provide more than 50% of the calories consumed globally, we constructed four international crop trade networks (iCTNs). We observed the increasing globalization in the international crop trade and different trade patterns in different iCTNs. The distributions of node degrees deviate from power laws, and the distributions of link weights follow power laws. We also found that the in-degree is positively correlated with the out-degree, but negatively correlated with the clustering coefficient. This indicates that the numbers of trade partners affect the tendency of economies to form clusters. In addition, each iCTN exhibits a unique topology which is different from the whole food network studied by many researchers. Our analysis on the microstructural characteristics of different iCTNs provides highly valuable insights into distinctive features of specific crop trades and has potential implications for model construction and food security. Full article
(This article belongs to the Special Issue Structure and Dynamics of Complex Socioeconomic Networks)
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29 pages, 5510 KiB  
Article
Nestedness-Based Measurement of Evolutionarily Stable Equilibrium of Global Production System
by Jiaqi Ren, Lizhi Xing, Yu Han and Xianlei Dong
Entropy 2021, 23(8), 1077; https://doi.org/10.3390/e23081077 - 19 Aug 2021
Cited by 3 | Viewed by 2843
Abstract
A nested structure is a structural feature that is conducive to system stability formed by the coevolution of biological species in mutualistic ecosystems The coopetition relationship and value flow between industrial sectors in the global value chain are similar to the mutualistic ecosystem [...] Read more.
A nested structure is a structural feature that is conducive to system stability formed by the coevolution of biological species in mutualistic ecosystems The coopetition relationship and value flow between industrial sectors in the global value chain are similar to the mutualistic ecosystem in nature. That is, the global economic system is always changing to form one dynamic equilibrium after another. In this paper, a nestedness-based analytical framework is used to define the generalist and specialist sectors for the purpose of analyzing the changes in the global supply pattern. We study why the global economic system can reach a stable equilibrium, what the role of different sectors play in the steady status, and how to enhance the stability of the global economic system. In detail, the domestic trade network, export trade network and import trade network of each country are extracted. Then, an econometric model is designed to analyze how the microstructure of the production system affects a country’s macroeconomic performance. Full article
(This article belongs to the Special Issue Structure and Dynamics of Complex Socioeconomic Networks)
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21 pages, 59014 KiB  
Article
Analyzing the Co-Competition Mechanism of High-Tech Park from the Perspective of Complex Socioeconomic Network
by Lizhi Xing, Yu Han and Jingying Xu
Entropy 2021, 23(8), 978; https://doi.org/10.3390/e23080978 - 29 Jul 2021
Cited by 2 | Viewed by 2649
Abstract
The fusion of “innovation theory” and “ecology” gave birth to a large number of studies on “innovation ecology”, which mainly studies how to build an industrial ecological chain at the regional level, focusing on self-evolution, achieving ecological balance, and enabling the regional economy [...] Read more.
The fusion of “innovation theory” and “ecology” gave birth to a large number of studies on “innovation ecology”, which mainly studies how to build an industrial ecological chain at the regional level, focusing on self-evolution, achieving ecological balance, and enabling the regional economy to take the path of sustainable innovation. This type of research borrows a lot of concepts from ecology and very vividly describes the competition and cooperation relationships formed by various agents in the innovation system, laying a good foundation for qualitative analysis of the inherent dynamics of innovation development. However, many studies focus on the analogous description of ecosystems and economic systems, lacking scientifically and rigorously quantitative empirical research as support. This paper uses network-based indicators such as degree, cluster coefficient, and betweenness centrality to measure the function and position of high-tech enterprises in the Z-Park of a business environment. In this way, we clarify the socioeconomic meaning of the topological structure of the regional innovation system. On this basis, it provides theoretical references for regional innovation development and sustainable development policy formulation. Full article
(This article belongs to the Special Issue Structure and Dynamics of Complex Socioeconomic Networks)
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