Pub Date : 2021-12-15DOI: 10.25088/complexsystems.30.4.441
Rinat Aynulin, P. Chebotarev
Proximity measures on graphs are extensively used for solving various problems in network analysis, including community detection. Previous studies have considered proximity measures mainly for networks without attributes. However, attribute information, node attributes in particular, allows a more in-depth exploration of the network structure. This paper extends the definition of a number of proximity measures to the case of attributed networks. To take node attributes into account, attribute similarity is embedded into the adjacency matrix. Obtained attribute-aware proximity measures are numerically studied in the context of community detection in real-world networks.
{"title":"Extending Proximity Measures to Attributed Networks for Community Detection","authors":"Rinat Aynulin, P. Chebotarev","doi":"10.25088/complexsystems.30.4.441","DOIUrl":"https://doi.org/10.25088/complexsystems.30.4.441","url":null,"abstract":"Proximity measures on graphs are extensively used for solving various problems in network analysis, including community detection. Previous studies have considered proximity measures mainly for networks without attributes. However, attribute information, node attributes in particular, allows a more in-depth exploration of the network structure. This paper extends the definition of a number of proximity measures to the case of attributed networks. To take node attributes into account, attribute similarity is embedded into the adjacency matrix. Obtained attribute-aware proximity measures are numerically studied in the context of community detection in real-world networks.","PeriodicalId":50871,"journal":{"name":"Advances in Complex Systems","volume":null,"pages":null},"PeriodicalIF":0.4,"publicationDate":"2021-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83103082","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-15DOI: 10.25088/complexsystems.30.4.513
K. Premalatha, R. Amuda, V. K. Chandrasekar, M. Senthilvelan, M. Lakshmanan
We investigate the existence of collective dynamical states in nonlocally coupled Stuart–Landau oscillators with symmetry breaking included in the coupling term. We find that the radius of nonlocal interaction and nonisochronicity parameter play important roles in identifying the swing of synchronized states through amplitude chimera states. Collective dynamical states are distinguished with the help of strength of incoherence. Different transition routes to multi-chimera death states are analyzed with respect to the nonlocal coupling radius. In addition, we investigate the existence of collective dynamical states including traveling wave state, amplitude chimera state and multi-chimera death state by introducing higher-order nonlinear terms in the system. We also verify the robustness of the given notable properties for the coupled system.
{"title":"Impact of Nonlocal Interaction on Chimera States in Nonlocally Coupled Stuart-Landau Oscillators","authors":"K. Premalatha, R. Amuda, V. K. Chandrasekar, M. Senthilvelan, M. Lakshmanan","doi":"10.25088/complexsystems.30.4.513","DOIUrl":"https://doi.org/10.25088/complexsystems.30.4.513","url":null,"abstract":"We investigate the existence of collective dynamical states in nonlocally coupled Stuart–Landau oscillators with symmetry breaking included in the coupling term. We find that the radius of nonlocal interaction and nonisochronicity parameter play important roles in identifying the swing of synchronized states through amplitude chimera states. Collective dynamical states are distinguished with the help of strength of incoherence. Different transition routes to multi-chimera death states are analyzed with respect to the nonlocal coupling radius. In addition, we investigate the existence of collective dynamical states including traveling wave state, amplitude chimera state and multi-chimera death state by introducing higher-order nonlinear terms in the system. We also verify the robustness of the given notable properties for the coupled system.","PeriodicalId":50871,"journal":{"name":"Advances in Complex Systems","volume":null,"pages":null},"PeriodicalIF":0.4,"publicationDate":"2021-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82583046","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-06DOI: 10.1142/S0219525923500017
Y. Tarasevich, A. V. Danilova, O. E. Romanovskaya
A network analysis of the structure of verbal communications in one of the most popular Russian novels of the Soviet era The Master and Margarita by Bulgakov has been carried out. The structure of the novel is complex (a story within a story). Moreover, the real-world-characters and the other-world-characters are interacting in the novel. This complex and unusual composition makes the novel especially attractive for a network analysis. In our study, only paired verbal communications (conversations) between explicitly present and acting characters have been taken into account. Based on a character pair verbal communication matrix, a graph has been constructed, the vertices of which are the characters of the novel, while the edges correspond to the connections between them. Taking only paired verbal communications into account leads to the result, that the character network can be described by an ordinary, rather than a directed graph. Since the activity of the conversations was out of our intended scope, the edges have been given no weights. The largest connected component of the graph consists of 76 characters. Centralities, such as degree, betweenness, closeness, eigenvector, and assortativity coefficient were computed to characterize the network. The structure of the communities in the network was also analysed. In addition to the obvious large communities-the characters from the Yershalaim part of the novel and the characters of the Moscow part-the analysis also revealed a fine structure in the Moscow component. Using the analysis of centralities, a group of main characters has been detected. The central characters of the novel are Koroviev, Margarita, Bezdomny, Woland, Behemoth, Azazello, Bosoi, Warenukha, Master, and Levi Matthew.
{"title":"Network Analysis of Verbal Communications in the Novel the Master and Margarita by M. A. Bulgakov","authors":"Y. Tarasevich, A. V. Danilova, O. E. Romanovskaya","doi":"10.1142/S0219525923500017","DOIUrl":"https://doi.org/10.1142/S0219525923500017","url":null,"abstract":"A network analysis of the structure of verbal communications in one of the most popular Russian novels of the Soviet era The Master and Margarita by Bulgakov has been carried out. The structure of the novel is complex (a story within a story). Moreover, the real-world-characters and the other-world-characters are interacting in the novel. This complex and unusual composition makes the novel especially attractive for a network analysis. In our study, only paired verbal communications (conversations) between explicitly present and acting characters have been taken into account. Based on a character pair verbal communication matrix, a graph has been constructed, the vertices of which are the characters of the novel, while the edges correspond to the connections between them. Taking only paired verbal communications into account leads to the result, that the character network can be described by an ordinary, rather than a directed graph. Since the activity of the conversations was out of our intended scope, the edges have been given no weights. The largest connected component of the graph consists of 76 characters. Centralities, such as degree, betweenness, closeness, eigenvector, and assortativity coefficient were computed to characterize the network. The structure of the communities in the network was also analysed. In addition to the obvious large communities-the characters from the Yershalaim part of the novel and the characters of the Moscow part-the analysis also revealed a fine structure in the Moscow component. Using the analysis of centralities, a group of main characters has been detected. The central characters of the novel are Koroviev, Margarita, Bezdomny, Woland, Behemoth, Azazello, Bosoi, Warenukha, Master, and Levi Matthew.","PeriodicalId":50871,"journal":{"name":"Advances in Complex Systems","volume":null,"pages":null},"PeriodicalIF":0.4,"publicationDate":"2021-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85524233","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-22DOI: 10.1142/S0219525921500077
José A. Morales, Jorge Flores, C. Gershenson, Carlos Pineda
Any collection can be ranked. Sports and games are common examples of ranked systems: players and teams are constantly ranked using different methods. The statistical properties of rankings have been studied for almost a century in a variety of fields. More recently, data availability has allowed us to study rank dynamics: how elements of a ranking change in time. Here, we study the rank distributions and rank dynamics of 12 datasets from different sports and games. To study rank dynamics, we consider measures that we have defined previously: rank diversity, change probability, rank entropy, and rank complexity. We also introduce a new measure that we call “system closure” that reflects how many elements enter or leave the rankings in time. We use a random walk model to reproduce the observed rank dynamics, showing that a simple mechanism can generate similar statistical properties as the ones observed in the datasets. Our results show that while rank distributions vary considerably for different rankings, rank dynamics have similar behaviors, independently of the nature and competitiveness of the sport or game and its ranking method. Our results also suggest that our measures of rank dynamics are general and applicable for complex systems of different natures.
{"title":"Statistical Properties of Rankings in Sports and Games","authors":"José A. Morales, Jorge Flores, C. Gershenson, Carlos Pineda","doi":"10.1142/S0219525921500077","DOIUrl":"https://doi.org/10.1142/S0219525921500077","url":null,"abstract":"Any collection can be ranked. Sports and games are common examples of ranked systems: players and teams are constantly ranked using different methods. The statistical properties of rankings have been studied for almost a century in a variety of fields. More recently, data availability has allowed us to study rank dynamics: how elements of a ranking change in time. Here, we study the rank distributions and rank dynamics of 12 datasets from different sports and games. To study rank dynamics, we consider measures that we have defined previously: rank diversity, change probability, rank entropy, and rank complexity. We also introduce a new measure that we call “system closure” that reflects how many elements enter or leave the rankings in time. We use a random walk model to reproduce the observed rank dynamics, showing that a simple mechanism can generate similar statistical properties as the ones observed in the datasets. Our results show that while rank distributions vary considerably for different rankings, rank dynamics have similar behaviors, independently of the nature and competitiveness of the sport or game and its ranking method. Our results also suggest that our measures of rank dynamics are general and applicable for complex systems of different natures.","PeriodicalId":50871,"journal":{"name":"Advances in Complex Systems","volume":null,"pages":null},"PeriodicalIF":0.4,"publicationDate":"2021-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87673651","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-18DOI: 10.1142/s0219525921400038
Emiliano Alvarez, J. Brida, Silvia London
{"title":"Abm Documentation and odd Protocol in Economics: a bibliometric Analysis","authors":"Emiliano Alvarez, J. Brida, Silvia London","doi":"10.1142/s0219525921400038","DOIUrl":"https://doi.org/10.1142/s0219525921400038","url":null,"abstract":"","PeriodicalId":50871,"journal":{"name":"Advances in Complex Systems","volume":null,"pages":null},"PeriodicalIF":0.4,"publicationDate":"2021-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83603762","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-13DOI: 10.1142/s0219525921400026
S. Edet, P. Panzarasa, M. Riccaboni
Recent studies on international networks have investigated the role of global cities as catalysts of knowledge flows. In this paper, we examine global cities in transnational networks of innovators. To assess the likelihood of scientists and inventors from different cities to take part in international teams, we propose a measure based on 3-hyperedges in the collaboration network constructed from scientific publications and patents. This measure is used to identify the most competitive global cities in the international network of innovators. To this end, we construct a null model based on the hypergeometric ensembles of random graphs. We find that five US cities play a leading role in transnational networks of innovators. Among them, San Francisco stands out as the most globalized city.
{"title":"Global Cities in International Networks of Innovators","authors":"S. Edet, P. Panzarasa, M. Riccaboni","doi":"10.1142/s0219525921400026","DOIUrl":"https://doi.org/10.1142/s0219525921400026","url":null,"abstract":"Recent studies on international networks have investigated the role of global cities as catalysts of knowledge flows. In this paper, we examine global cities in transnational networks of innovators. To assess the likelihood of scientists and inventors from different cities to take part in international teams, we propose a measure based on 3-hyperedges in the collaboration network constructed from scientific publications and patents. This measure is used to identify the most competitive global cities in the international network of innovators. To this end, we construct a null model based on the hypergeometric ensembles of random graphs. We find that five US cities play a leading role in transnational networks of innovators. Among them, San Francisco stands out as the most globalized city.","PeriodicalId":50871,"journal":{"name":"Advances in Complex Systems","volume":null,"pages":null},"PeriodicalIF":0.4,"publicationDate":"2021-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84712434","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-12DOI: 10.1142/s0219525921500090
Giulia Braghini, F. Salvarani
{"title":"Effects of Hidden Opinion manipulation in Microblogging Platforms","authors":"Giulia Braghini, F. Salvarani","doi":"10.1142/s0219525921500090","DOIUrl":"https://doi.org/10.1142/s0219525921500090","url":null,"abstract":"","PeriodicalId":50871,"journal":{"name":"Advances in Complex Systems","volume":null,"pages":null},"PeriodicalIF":0.4,"publicationDate":"2021-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90985061","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-01DOI: 10.1142/s0219525921500089
A. M. Jaramillo, Mariana Macedo, R. Menezes
{"title":"Reaching to the Top: the Gender effect in Highly-Ranked academics in Computer Science","authors":"A. M. Jaramillo, Mariana Macedo, R. Menezes","doi":"10.1142/s0219525921500089","DOIUrl":"https://doi.org/10.1142/s0219525921500089","url":null,"abstract":"","PeriodicalId":50871,"journal":{"name":"Advances in Complex Systems","volume":null,"pages":null},"PeriodicalIF":0.4,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87021426","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-30DOI: 10.1142/s021952592150003x
WILMER LEAL, GUILLERMO RESTREPO, PETER F. STADLER, JÜRGEN JOST
Hypergraphs serve as models of complex networks that capture more general structures than binary relations. For graphs, a wide array of statistics has been devised to gauge different aspects of their structures. Hypergraphs lack behind in this respect. The Forman–Ricci curvature is a statistics for graphs based on Riemannian geometry, which stresses the relational character of vertices in a network by focusing on the edges rather than on the vertices. Despite many successful applications of this measure to graphs, Forman–Ricci curvature has not been introduced for hypergraphs. Here, we define the Forman–Ricci curvature for directed and undirected hypergraphs such that the curvature for graphs is recovered as a special case. It quantifies the trade-off between hyperedge (arc) size and the degree of participation of hyperedge (arc) vertices in other hyperedges (arcs). Here, we determine upper and lower bounds for Forman–Ricci curvature both for hypergraphs in general and for graphs in particular. The measure is then applied to two large networks: the Wikipedia vote network and the metabolic network of the bacterium Escherichia coli. In the first case, the curvature is governed by the size of the hyperedges, while in the second example, it is dominated by the hyperedge degree. We found that the number of users involved in Wikipedia elections goes hand-in-hand with the participation of experienced users. The curvature values of the metabolic network allowed detecting redundant and bottle neck reactions. It is found that ADP phosphorylation is the metabolic bottle neck reaction but that the reverse reaction is not similarly central for the metabolism. Furthermore, we show the utility of the Forman–Ricci curvature for quantification of assortativity in hypergraphs and illustrate the idea by investigating three metabolic networks.
{"title":"FORMAN–RICCI CURVATURE FOR HYPERGRAPHS","authors":"WILMER LEAL, GUILLERMO RESTREPO, PETER F. STADLER, JÜRGEN JOST","doi":"10.1142/s021952592150003x","DOIUrl":"https://doi.org/10.1142/s021952592150003x","url":null,"abstract":"Hypergraphs serve as models of complex networks that capture more general structures than binary relations. For graphs, a wide array of statistics has been devised to gauge different aspects of their structures. Hypergraphs lack behind in this respect. The Forman–Ricci curvature is a statistics for graphs based on Riemannian geometry, which stresses the relational character of vertices in a network by focusing on the edges rather than on the vertices. Despite many successful applications of this measure to graphs, Forman–Ricci curvature has not been introduced for hypergraphs. Here, we define the Forman–Ricci curvature for directed and undirected hypergraphs such that the curvature for graphs is recovered as a special case. It quantifies the trade-off between hyperedge (arc) size and the degree of participation of hyperedge (arc) vertices in other hyperedges (arcs). Here, we determine upper and lower bounds for Forman–Ricci curvature both for hypergraphs in general and for graphs in particular. The measure is then applied to two large networks: the Wikipedia vote network and the metabolic network of the bacterium <italic>Escherichia coli</italic>. In the first case, the curvature is governed by the size of the hyperedges, while in the second example, it is dominated by the hyperedge degree. We found that the number of users involved in Wikipedia elections goes hand-in-hand with the participation of experienced users. The curvature values of the metabolic network allowed detecting redundant and bottle neck reactions. It is found that ADP phosphorylation is the metabolic bottle neck reaction but that the reverse reaction is not similarly central for the metabolism. Furthermore, we show the utility of the Forman–Ricci curvature for quantification of assortativity in hypergraphs and illustrate the idea by investigating three metabolic networks.","PeriodicalId":50871,"journal":{"name":"Advances in Complex Systems","volume":null,"pages":null},"PeriodicalIF":0.4,"publicationDate":"2021-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138515760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-25DOI: 10.1142/s0219525921500041
Shaoping Xiao, B. She, S. Mehta, Z. Kan
In many engineered and natural networked systems, there has been great interest in leader selection and/or edge assignment during the optimal design of controllable networks. In this paper, we present our pioneering work in leader–follower network design via memetic algorithms, which focuses on minimizing the number of leaders or the amount of control energy while ensuring network controllability. We consider three problems in this paper: (1) selecting the minimum number of leaders in a pre-defined network with guaranteed network controllability; (2) selecting the leaders in a pre-defined network with the minimum control energy; and (3) assigning edges (interactions) between nodes to form a controllable leader–follower network with the minimum control energy. The proposed framework can be applied in designing signed, unsigned, directed, or undirected networks. It should be noted that this work is the first to apply memetic algorithms in the design of controllable networks. We chose memetic algorithms because they have been shown to be more efficient and more effective than the standard genetic algorithms in solving some optimization problems. Our simulation results provide an additional demonstration of their efficiency and effectiveness.
{"title":"Design of controllable Leader-follower Networks via Memetic Algorithms","authors":"Shaoping Xiao, B. She, S. Mehta, Z. Kan","doi":"10.1142/s0219525921500041","DOIUrl":"https://doi.org/10.1142/s0219525921500041","url":null,"abstract":"In many engineered and natural networked systems, there has been great interest in leader selection and/or edge assignment during the optimal design of controllable networks. In this paper, we present our pioneering work in leader–follower network design via memetic algorithms, which focuses on minimizing the number of leaders or the amount of control energy while ensuring network controllability. We consider three problems in this paper: (1) selecting the minimum number of leaders in a pre-defined network with guaranteed network controllability; (2) selecting the leaders in a pre-defined network with the minimum control energy; and (3) assigning edges (interactions) between nodes to form a controllable leader–follower network with the minimum control energy. The proposed framework can be applied in designing signed, unsigned, directed, or undirected networks. It should be noted that this work is the first to apply memetic algorithms in the design of controllable networks. We chose memetic algorithms because they have been shown to be more efficient and more effective than the standard genetic algorithms in solving some optimization problems. Our simulation results provide an additional demonstration of their efficiency and effectiveness.","PeriodicalId":50871,"journal":{"name":"Advances in Complex Systems","volume":null,"pages":null},"PeriodicalIF":0.4,"publicationDate":"2021-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90666540","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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