Pub Date : 2025-02-01DOI: 10.1016/j.physa.2024.130318
Massimiliano Zanin
In the last decade, statistical physics has joined the effort of the scientific community in the endeavour of understanding the structure and dynamics of air transport delay propagation, especially through the reconstruction and analysis of functional networks. While being a powerful instrument, such networks rely on the availability of large quantities of real data, and can only be used to describe historical dynamics. This contribution presents an alternative way of analysing public delay data, based on minimal information and a set of hypotheses about why and where observed delays had to be generated. We show how this analysis allows recovering known behaviours of the system, as the dependence of delays on the saturation of the arrival airport; but also how local and network propagation patterns can be detected ahead of time.
{"title":"Reconstructing functional networks of air transport delay propagations with minimal information","authors":"Massimiliano Zanin","doi":"10.1016/j.physa.2024.130318","DOIUrl":"10.1016/j.physa.2024.130318","url":null,"abstract":"<div><div>In the last decade, statistical physics has joined the effort of the scientific community in the endeavour of understanding the structure and dynamics of air transport delay propagation, especially through the reconstruction and analysis of functional networks. While being a powerful instrument, such networks rely on the availability of large quantities of real data, and can only be used to describe historical dynamics. This contribution presents an alternative way of analysing public delay data, based on minimal information and a set of hypotheses about why and where observed delays had to be generated. We show how this analysis allows recovering known behaviours of the system, as the dependence of delays on the saturation of the arrival airport; but also how local and network propagation patterns can be detected ahead of time.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"659 ","pages":"Article 130318"},"PeriodicalIF":2.8,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143160748","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-01DOI: 10.1016/j.physa.2024.130335
Ignacio A. Perez, Cristian E. La Rocca
Extensive research has focused on studying the robustness of interdependent non-directed networks and the design of mitigation strategies aimed at reducing disruptions caused by cascading failures. However, real systems such as power and communication networks are directed, which underscores the necessity of broadening the analysis by including directed networks. In this work, we develop an analytical framework to study a recovery strategy in two interdependent directed networks in which a fraction of nodes in each network have single dependencies with nodes in the other network. Following the random failure of nodes that leaves a fraction intact, we repair a fraction of nodes that are neighbors of the giant strongly connected component of each network with probability or recovery success rate . Our analysis reveals an abrupt transition between total system collapse and complete recovery as is increased. As a consequence, we identify three distinct phases in the parameter space: collapse despite intervention, recovery enabled by the strategy, and resilience without intervention. Moreover, we demonstrate our strategy on a system built from empirical data and find that it can save resources compared to a random recovery strategy. Our findings underscore the potential of targeted recovery strategies to enhance the robustness of real interdependent directed networks against cascading failures.
{"title":"Recovery of contour nodes in interdependent directed networks","authors":"Ignacio A. Perez, Cristian E. La Rocca","doi":"10.1016/j.physa.2024.130335","DOIUrl":"10.1016/j.physa.2024.130335","url":null,"abstract":"<div><div>Extensive research has focused on studying the robustness of interdependent non-directed networks and the design of mitigation strategies aimed at reducing disruptions caused by cascading failures. However, real systems such as power and communication networks are directed, which underscores the necessity of broadening the analysis by including directed networks. In this work, we develop an analytical framework to study a recovery strategy in two interdependent directed networks in which a fraction <span><math><mi>q</mi></math></span> of nodes in each network have single dependencies with nodes in the other network. Following the random failure of nodes that leaves a fraction <span><math><mi>p</mi></math></span> intact, we repair a fraction of nodes that are neighbors of the giant strongly connected component of each network with probability or recovery success rate <span><math><mi>γ</mi></math></span>. Our analysis reveals an abrupt transition between total system collapse and complete recovery as <span><math><mi>p</mi></math></span> is increased. As a consequence, we identify three distinct phases in the <span><math><mrow><mo>(</mo><mi>p</mi><mo>,</mo><mi>γ</mi><mo>)</mo></mrow></math></span> parameter space: collapse despite intervention, recovery enabled by the strategy, and resilience without intervention. Moreover, we demonstrate our strategy on a system built from empirical data and find that it can save resources compared to a random recovery strategy. Our findings underscore the potential of targeted recovery strategies to enhance the robustness of real interdependent directed networks against cascading failures.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"659 ","pages":"Article 130335"},"PeriodicalIF":2.8,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143161215","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-01DOI: 10.1016/j.physa.2024.130321
Ai-Wen Li , Ya-Fang Liu , Jian-Lin Zhou , An Zeng , Xiao-Ke Xu , Ying Fan
Signed social networks are a special type of social network with positive and negative relationships. It can provide a powerful framework for studying information spreading in light of opposite user relationships. Currently, static immunization strategies have been constructed to control the spread of disinformation on signed social networks. Here, we focus on dynamic immunization that can be real-time immune to the spread of disinformation on signed social networks, which is vital for shaping public discourse and opinion formation. Accordingly, we proposed the signed contact-tracing (SCT) considering the opposite attitudes of users toward information. Experiments with synthetic and empirical signed networks explore the impact of signed network structure with positive and negative edges on dynamic immunity and confirm the necessity of considering signs in the dynamic immune process. Then, the effectiveness of SCT was verified by two evaluation indicators, and find that targeting individuals with the same ideological group has a smaller spreading range and lower spreading speed than those without differentiated attitudes. Furthermore, the signed backward-contact-tracing (SBCT) based on SCT optimization offers optimal regulatory recommendations for enhancing immunity against disinformation in signed social networks. The study demonstrates how negative relationships impact the dynamic immunity of disinformation, and improves the application of dynamic immunity strategies in signed networks.
{"title":"Dynamic immunization for disinformation spreading on signed social networks","authors":"Ai-Wen Li , Ya-Fang Liu , Jian-Lin Zhou , An Zeng , Xiao-Ke Xu , Ying Fan","doi":"10.1016/j.physa.2024.130321","DOIUrl":"10.1016/j.physa.2024.130321","url":null,"abstract":"<div><div>Signed social networks are a special type of social network with positive and negative relationships. It can provide a powerful framework for studying information spreading in light of opposite user relationships. Currently, static immunization strategies have been constructed to control the spread of disinformation on signed social networks. Here, we focus on dynamic immunization that can be real-time immune to the spread of disinformation on signed social networks, which is vital for shaping public discourse and opinion formation. Accordingly, we proposed the signed contact-tracing (SCT) considering the opposite attitudes of users toward information. Experiments with synthetic and empirical signed networks explore the impact of signed network structure with positive and negative edges on dynamic immunity and confirm the necessity of considering signs in the dynamic immune process. Then, the effectiveness of SCT was verified by two evaluation indicators, and find that targeting individuals with the same ideological group has a smaller spreading range and lower spreading speed than those without differentiated attitudes. Furthermore, the signed backward-contact-tracing (SBCT) based on SCT optimization offers optimal regulatory recommendations for enhancing immunity against disinformation in signed social networks. The study demonstrates how negative relationships impact the dynamic immunity of disinformation, and improves the application of dynamic immunity strategies in signed networks.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"659 ","pages":"Article 130321"},"PeriodicalIF":2.8,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143161292","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The role of social media platforms, where opinions form and are shared, in stock market movements is becoming increasingly important. Several past studies have demonstrated the predictive power of web-based information analysis on investor sentiment and opinion. This paper analyzes the present relationship between discussions on X (previously known as Twitter) and market movements. Additionally, we contribute to the existing body of knowledge by introducing novel approaches grounded in information theory. Through empirical analysis and advanced statistical techniques, our study sheds light on the continued influence of social media sentiment on stock price returns, providing valuable insights for investors and market analysts navigating the complexities of modern financial markets.
{"title":"Social media discussions anticipates financial market volumes","authors":"Giulio Vicentini , Alessandro Nucci , Guido Caldarelli , Elisa Omodei","doi":"10.1016/j.physa.2025.130388","DOIUrl":"10.1016/j.physa.2025.130388","url":null,"abstract":"<div><div>The role of social media platforms, where opinions form and are shared, in stock market movements is becoming increasingly important. Several past studies have demonstrated the predictive power of web-based information analysis on investor sentiment and opinion. This paper analyzes the present relationship between discussions on X (previously known as Twitter) and market movements. Additionally, we contribute to the existing body of knowledge by introducing novel approaches grounded in information theory. Through empirical analysis and advanced statistical techniques, our study sheds light on the continued influence of social media sentiment on stock price returns, providing valuable insights for investors and market analysts navigating the complexities of modern financial markets.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"661 ","pages":"Article 130388"},"PeriodicalIF":2.8,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143271418","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-01DOI: 10.1016/j.physa.2024.130314
C.M.C. Inacio Jr , Ladislav Kristoufek , S.A. David
This paper investigates the dynamic interrelationships between West Texas Intermediate (WTI) prices and various energy commodities including Brent crude oil futures, Brent spot prices, American diesel futures, and the Reformulated Blendstock for Oxygenate Blending, across four critical periods surrounding the Covid-19 pandemic and the Russia–Ukraine conflict. Employing the Multifractal Detrended Fluctuation Cross-Correlation Analysis (MFXDFA) methodology, the study analyzes both the static and dynamic Hurst exponents to examine the multifractal behaviors of these price relationships. Results indicate a pronounced increase in price persistence during the height of the Covid-19 pandemic, with a subsequent decrease during the Russia–Ukraine conflict, suggesting a shift toward a new price dynamic influenced by recent global crises. This research contributes to understanding the evolving dynamics in crude oil and refined products markets, shedding light on how major geopolitical and global health events can reshape market behavior and pricing structures in significant ways.
{"title":"Dynamic price interactions in energy commodities benchmarks: Insights from multifractal analysis during crisis periods","authors":"C.M.C. Inacio Jr , Ladislav Kristoufek , S.A. David","doi":"10.1016/j.physa.2024.130314","DOIUrl":"10.1016/j.physa.2024.130314","url":null,"abstract":"<div><div>This paper investigates the dynamic interrelationships between West Texas Intermediate (WTI) prices and various energy commodities including Brent crude oil futures, Brent spot prices, American diesel futures, and the Reformulated Blendstock for Oxygenate Blending, across four critical periods surrounding the Covid-19 pandemic and the Russia–Ukraine conflict. Employing the Multifractal Detrended Fluctuation Cross-Correlation Analysis (MFXDFA) methodology, the study analyzes both the static and dynamic Hurst exponents to examine the multifractal behaviors of these price relationships. Results indicate a pronounced increase in price persistence during the height of the Covid-19 pandemic, with a subsequent decrease during the Russia–Ukraine conflict, suggesting a shift toward a new price dynamic influenced by recent global crises. This research contributes to understanding the evolving dynamics in crude oil and refined products markets, shedding light on how major geopolitical and global health events can reshape market behavior and pricing structures in significant ways.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"659 ","pages":"Article 130314"},"PeriodicalIF":2.8,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143160681","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We analyze the Shannon and Fisher information measures for systems subjected to quartic and symmetric potential wells. The wave functions are obtained by solving the time-independent Schrödinger equation, using aspects of perturbation theory. We examine how the information for various quantum states evolves with changes in the width of the potential well. For both potentials, the Shannon entropy decreases in position space and increases in momentum space as the width increases, maintaining a constant sum of entropies, consistent with Heisenberg’s uncertainty principle. The Fisher information measure shows different behaviors for the two potentials: it remains nearly constant for the quartic potential. For the symmetric well potential, the Fisher information decreases in position space and increases in momentum space as localization in position space increases, also consistent with the analogue of Heisenberg’s uncertainty principle. Additionally, the Bialynicki–Birula–Mycielski inequality is evaluated across various cases and is confirmed to hold in each instance.
{"title":"Quantum information measures in quartic and symmetric potentials using perturbative approach","authors":"Vikash Kumar Ojha , Ramkumar Radhakrishnan , Mariyah Ughradar","doi":"10.1016/j.physa.2024.130346","DOIUrl":"10.1016/j.physa.2024.130346","url":null,"abstract":"<div><div>We analyze the Shannon and Fisher information measures for systems subjected to quartic and symmetric potential wells. The wave functions are obtained by solving the time-independent Schrödinger equation, using aspects of perturbation theory. We examine how the information for various quantum states evolves with changes in the width of the potential well. For both potentials, the Shannon entropy decreases in position space and increases in momentum space as the width increases, maintaining a constant sum of entropies, consistent with Heisenberg’s uncertainty principle. The Fisher information measure shows different behaviors for the two potentials: it remains nearly constant for the quartic potential. For the symmetric well potential, the Fisher information decreases in position space and increases in momentum space as localization in position space increases, also consistent with the analogue of Heisenberg’s uncertainty principle. Additionally, the Bialynicki–Birula–Mycielski inequality is evaluated across various cases and is confirmed to hold in each instance.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"659 ","pages":"Article 130346"},"PeriodicalIF":2.8,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143161216","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-01DOI: 10.1016/j.physa.2024.130337
Zhijie Zhao , Qichen Shi , Yong Liu
In this paper, an improved model of fish collective behavior is proposed, which combines social interactions with the risk perception and startle cascades behavior. By modeling the fast-start of fish individual and the startle propagation processes in fish school, the sudden collective evasion phenomenon during the fish collective behavior is studied. Utilizing this model, the paper focuses on investigating the impacts of cluster patterns and individual heterogeneity in social behavior and risk perception on the collective evasion process through simulations. The results show that the density of cluster aggregation is crucial in determining the propagation capability of startle responses. Conversely, the sudden startle propagation may completely change the type of cluster pattern for the cases in transitional zones. In some scenarios, a very small number of behaviorally heterogeneous individuals can dominate the cluster pattern of the entire group. Finally, it is found that distributing individuals with strong perception abilities around the periphery of the group while clustering those with weaker perception abilities within the inner group enhances the overall perception ability of the entire group.
{"title":"Modeling and simulation of the fish collective behavior with risk perception and startle cascades","authors":"Zhijie Zhao , Qichen Shi , Yong Liu","doi":"10.1016/j.physa.2024.130337","DOIUrl":"10.1016/j.physa.2024.130337","url":null,"abstract":"<div><div>In this paper, an improved model of fish collective behavior is proposed, which combines social interactions with the risk perception and startle cascades behavior. By modeling the fast-start of fish individual and the startle propagation processes in fish school, the sudden collective evasion phenomenon during the fish collective behavior is studied. Utilizing this model, the paper focuses on investigating the impacts of cluster patterns and individual heterogeneity in social behavior and risk perception on the collective evasion process through simulations. The results show that the density of cluster aggregation is crucial in determining the propagation capability of startle responses. Conversely, the sudden startle propagation may completely change the type of cluster pattern for the cases in transitional zones. In some scenarios, a very small number of behaviorally heterogeneous individuals can dominate the cluster pattern of the entire group. Finally, it is found that distributing individuals with strong perception abilities around the periphery of the group while clustering those with weaker perception abilities within the inner group enhances the overall perception ability of the entire group.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"659 ","pages":"Article 130337"},"PeriodicalIF":2.8,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143160749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-01DOI: 10.1016/j.physa.2024.130320
Izabela S̀liwa , Pavel V. Maslennikov , Alex V. Zakharov
Statistical–mechanical theory based on the concept of the mean-force potentials is applied for description of the anchoring transitions in the liquid crystal system near a solid surface. This approach took into account not only the two-particle correlations between the nearest and next-nearest neighbors, but also the surface attractive interactions. The calculations have been carried out for cubic close packing with the Gay–Berne intermolecular potential interaction and with a (9-3)-like orientation-dependent molecule–wall interaction. Our calculations show that the number of surface layers to be taken into account depends more on the nature of interparticle correlations in the system than on the direct interaction of the wall with the nematic. It has been shown that there are several scenarios for anchoring transitions in such systems in a certain temperature and volume range.
{"title":"Anchoring transitions in a liquid crystal film near the interacting wall: A mean-force potentials approach","authors":"Izabela S̀liwa , Pavel V. Maslennikov , Alex V. Zakharov","doi":"10.1016/j.physa.2024.130320","DOIUrl":"10.1016/j.physa.2024.130320","url":null,"abstract":"<div><div>Statistical–mechanical theory based on the concept of the mean-force potentials is applied for description of the anchoring transitions in the liquid crystal system near a solid surface. This approach took into account not only the two-particle correlations between the nearest and next-nearest neighbors, but also the surface attractive interactions. The calculations have been carried out for cubic close packing with the Gay–Berne intermolecular potential interaction and with a (9-3)-like orientation-dependent molecule–wall interaction. Our calculations show that the number of surface layers to be taken into account depends more on the nature of interparticle correlations in the system than on the direct interaction of the wall with the nematic. It has been shown that there are several scenarios for anchoring transitions in such systems in a certain temperature and volume range.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"659 ","pages":"Article 130320"},"PeriodicalIF":2.8,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143160752","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-01DOI: 10.1016/j.physa.2024.130326
E. Jurčišinová, M. Jurčišin
The so-called 3-star kagome-like recursive-lattice approximation is introduced that significantly more accurately approximates the basic geometric structure of the real two-dimensional kagome lattice. The exact solution of the antiferromagnetic Ising model in the external magnetic field and with the presence of the three-site interaction within each elementary triangle of the introduced recursive lattice is found. The free energy of the model is derived and the system of all ground states is determined. The exact expressions for the residual entropies and magnetization values of all ground states of the model are derived. The magnetic and thermodynamic properties of the model are discussed in detail and are compared to those obtained in the framework of the lower recursive-lattice approximations of the model as well as to the existing exact results on the real kagome lattice. The performed analysis, on the one hand, confirms the validity of two early stated hypotheses about the behavior of residual entropies and magnetization properties of all ground states of frustrated magnetic systems on the recursive lattices and, on the other hand, allows one to make also nontrivial conclusions about the fundamental properties of the model on the real kagome lattice although the corresponding exact solutions are still not available. Last but not least, the performed analysis once again confirms the effectiveness of the recursive-lattice technique for the analysis of frustrated magnetic systems.
{"title":"Kagome antiferromagnet with the multisite interaction in the external magnetic field: Exact results within higher recursive-lattice approximation","authors":"E. Jurčišinová, M. Jurčišin","doi":"10.1016/j.physa.2024.130326","DOIUrl":"10.1016/j.physa.2024.130326","url":null,"abstract":"<div><div>The so-called 3-star kagome-like recursive-lattice approximation is introduced that significantly more accurately approximates the basic geometric structure of the real two-dimensional kagome lattice. The exact solution of the antiferromagnetic Ising model in the external magnetic field and with the presence of the three-site interaction within each elementary triangle of the introduced recursive lattice is found. The free energy of the model is derived and the system of all ground states is determined. The exact expressions for the residual entropies and magnetization values of all ground states of the model are derived. The magnetic and thermodynamic properties of the model are discussed in detail and are compared to those obtained in the framework of the lower recursive-lattice approximations of the model as well as to the existing exact results on the real kagome lattice. The performed analysis, on the one hand, confirms the validity of two early stated hypotheses about the behavior of residual entropies and magnetization properties of all ground states of frustrated magnetic systems on the recursive lattices and, on the other hand, allows one to make also nontrivial conclusions about the fundamental properties of the model on the real kagome lattice although the corresponding exact solutions are still not available. Last but not least, the performed analysis once again confirms the effectiveness of the recursive-lattice technique for the analysis of frustrated magnetic systems.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"659 ","pages":"Article 130326"},"PeriodicalIF":2.8,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143161212","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-01DOI: 10.1016/j.physa.2024.130328
Zhao-Long Hu , Qichao Jin , Lei Sun , Shuilin Peng
Borrowing and lending between banks and firms is the main channel of financial risk propagation, and there have been a number of studies on risk propagation and identification from the financial perspective. Despite complex networks are used as an important analytical tool for risk propagation in the financial system, there are few studies on analyzing financial risk source identification from the perspective of complex networks. With the help of complex network theory, we establish a multi-layer dynamic network between banks and firms, and propose an improved label propagation method for source identification based on the node degree, and this method can be applied to source identification under conditions of incomplete observation. A series of simulation experiments show that the proposed method exhibits a significant advantage in identifying the propagation source of financial risk compared with the original label propagation method. A key conclusion is that when targeting nodes with the highest out-degree, highest in-degree, highest total assets, or highest lent assets, our method encounters significant difficulties in identifying the propagation sources. Conversely, employing an opposite strategy allows us to accurately pinpoint these sources. Moreover, we find that the accuracy of source identification is mainly affected by the proportion of unobserved nodes, while the number of sources and the average connectivity of the network have relatively little effect. This study provides a new perspective for the study of risk propagation identification in financial network systems.
{"title":"Source identification on financial networks with label propagation","authors":"Zhao-Long Hu , Qichao Jin , Lei Sun , Shuilin Peng","doi":"10.1016/j.physa.2024.130328","DOIUrl":"10.1016/j.physa.2024.130328","url":null,"abstract":"<div><div>Borrowing and lending between banks and firms is the main channel of financial risk propagation, and there have been a number of studies on risk propagation and identification from the financial perspective. Despite complex networks are used as an important analytical tool for risk propagation in the financial system, there are few studies on analyzing financial risk source identification from the perspective of complex networks. With the help of complex network theory, we establish a multi-layer dynamic network between banks and firms, and propose an improved label propagation method for source identification based on the node degree, and this method can be applied to source identification under conditions of incomplete observation. A series of simulation experiments show that the proposed method exhibits a significant advantage in identifying the propagation source of financial risk compared with the original label propagation method. A key conclusion is that when targeting nodes with the highest out-degree, highest in-degree, highest total assets, or highest lent assets, our method encounters significant difficulties in identifying the propagation sources. Conversely, employing an opposite strategy allows us to accurately pinpoint these sources. Moreover, we find that the accuracy of source identification is mainly affected by the proportion of unobserved nodes, while the number of sources and the average connectivity of the network have relatively little effect. This study provides a new perspective for the study of risk propagation identification in financial network systems.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"659 ","pages":"Article 130328"},"PeriodicalIF":2.8,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143161253","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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