Network Science最新文献_第2页

Business transactions and ownership ties between firms 企业之间的商业交易和所有权关系

Network Science Pub Date : 2023-10-16 DOI: 10.1017/nws.2023.19

László Lőrincz, Sándor Juhász, Rebeka O. Szabó

引用次数: 0

Do NBA teams avoid trading within their own division? NBA球队会避免在自己的赛区进行交易吗?

Network Science Pub Date : 2023-09-18 DOI: 10.1017/nws.2023.18

jimi adams, Michał Bojanowski

引用次数: 0

Colorful path detection in vertex-colored temporal 彩色路径检测在顶点彩色时间

IF 1.7

Network Science Pub Date : 2023-08-18 DOI: 10.1017/nws.2023.17

R. Dondi, M. Hosseinzadeh

引用次数: 0

Limited evidence for structural balance in the family 家庭结构平衡的证据有限

IF 1.7

Network Science Pub Date : 2023-08-17 DOI: 10.1017/nws.2023.15

Jonas Stein, Jornt J. Mandemakers, A. van de Rijt

引用次数: 0

A general model for how attributes can reduce polarization in social groups 属性如何减少社会群体两极分化的通用模型

IF 1.7

Network Science Pub Date : 2023-07-24 DOI: 10.1017/nws.2023.13

Piotr J. Górski, Curtis Atkisson, J. Hołyst

{"title":"A general model for how attributes can reduce polarization in social groups","authors":"Piotr J. Górski, Curtis Atkisson, J. Hołyst","doi":"10.1017/nws.2023.13","DOIUrl":"https://doi.org/10.1017/nws.2023.13","url":null,"abstract":"\u0000 Polarization makes it difficult to form positive relationships across existing groups. Decreasing polarization may improve political discourse around the world. Polarization can be modeled on a social network as structural balance, where the network is composed of groups with positive links between all individuals in the group and negative links with all others. Previous work shows that incorporating attributes of individuals usually makes structural balance, and hence polarization, harder to achieve. That work examines only a limited number and types of attributes. We present a generalized model and a simulation framework to analyze the effect of any type of attribute, including analytically as long as an expected value can be written for the type of attribute. As attributes, we consider people’s (approximately) immutable characteristics (e.g., race, wealth) and such opinions that change more slowly than relationships (e.g., political preferences). We detail and analyze five classes of attributes, recapitulating the results of previous work in this framework and extending it. While it is easier to prevent than to destabilize polarization, we find that usually the most effective at both are continuous attributes, followed by ordered attributes and, finally, binary attributes. The effectiveness of unordered attributes varies depending on the magnitude of negative impact of having differing attributes but is smaller than of continuous ones. Testing the framework on network structures containing communities revealed that destroying polarization may require introducing local tensions. This model could be used by policymakers, among others, to prevent and design effective interventions to counteract polarization.","PeriodicalId":51827,"journal":{"name":"Network Science","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46345063","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Transitions between peace and systemic war as bifurcations in a signed network dynamical system 和平与系统性战争之间的过渡是一个有符号网络动力系统的分岔

Network Science Pub Date : 2023-06-21 DOI: 10.1017/nws.2023.10

Megan Morrison, J. Nathan Kutz, Michael Gabbay

{"title":"Transitions between peace and systemic war as bifurcations in a signed network dynamical system","authors":"Megan Morrison, J. Nathan Kutz, Michael Gabbay","doi":"10.1017/nws.2023.10","DOIUrl":"https://doi.org/10.1017/nws.2023.10","url":null,"abstract":"Abstract We investigate structural features and processes associated with the onset of systemic conflict using an approach which integrates complex systems theory with network modeling and analysis. We present a signed network model of cooperation and conflict dynamics in the context of international relations between states. The model evolves ties between nodes under the influence of a structural balance force and a dyad-specific force. Model simulations exhibit a sharp bifurcation from peace to systemic war as structural balance pressures increase, a bistable regime in which both peace and war stable equilibria exist, and a hysteretic reverse bifurcation from war to peace. We show how the analytical expression we derive for the peace-to-war bifurcation condition implies that polarized network structure increases susceptibility to systemic war. We develop a framework for identifying patterns of relationship perturbations that are most destabilizing and apply it to the network of European great powers before World War I. We also show that the model exhibits critical slowing down, in which perturbations to the peace equilibrium take longer to decay as the system draws closer to the bifurcation. We discuss how our results relate to international relations theories on the causes and catalysts of systemic war.","PeriodicalId":51827,"journal":{"name":"Network Science","volume":"313 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136355224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Exact recovery of Granger causality graphs with unconditional pairwise tests 无条件两两检验格兰杰因果图的精确恢复

IF 1.7

Network Science Pub Date : 2023-06-06 DOI: 10.1017/nws.2023.11

R. Kinnear, R. Mazumdar

{"title":"Exact recovery of Granger causality graphs with unconditional pairwise tests","authors":"R. Kinnear, R. Mazumdar","doi":"10.1017/nws.2023.11","DOIUrl":"https://doi.org/10.1017/nws.2023.11","url":null,"abstract":"\u0000 We study Granger Causality in the context of wide-sense stationary time series. The focus of the analysis is to understand how the underlying topological structure of the causality graph affects graph recovery by means of the pairwise testing heuristic. Our main theoretical result establishes a sufficient condition (in particular, the graph must satisfy a polytree assumption we refer to as strong causality) under which the graph can be recovered by means of unconditional and binary pairwise causality testing. Examples from the gene regulatory network literature are provided which establish that graphs which are strongly causal, or very nearly so, can be expected to arise in practice. We implement finite sample heuristics derived from our theory, and use simulation to compare our pairwise testing heuristic against LASSO-based methods. These simulations show that, for graphs which are strongly causal (or small perturbations thereof) the pairwise testing heuristic is able to more accurately recover the underlying graph. We show that the algorithm is scalable to graphs with thousands of nodes, and that, as long as structural assumptions are met, exhibits similar high-dimensional scaling properties as the LASSO. That is, performance degrades slowly while the system size increases and the number of available samples is held fixed. Finally, a proof-of-concept application example shows, by attempting to classify alcoholic individuals using only Granger causality graphs inferred from EEG measurements, that the inferred Granger causality graph topology carries identifiable features.","PeriodicalId":51827,"journal":{"name":"Network Science","volume":"11 1","pages":"431-457"},"PeriodicalIF":1.7,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"57043628","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Modeling complex interactions in a disrupted environment: Relational events in the WTC response 在被破坏的环境中建模复杂的相互作用:WTC响应中的关系事件

Network Science Pub Date : 2023-04-18 DOI: 10.1017/nws.2023.4

Scott Leo Renshaw, Selena M. Livas, Miruna G. Petrescu-Prahova, Carter T. Butts

{"title":"Modeling complex interactions in a disrupted environment: Relational events in the WTC response","authors":"Scott Leo Renshaw, Selena M. Livas, Miruna G. Petrescu-Prahova, Carter T. Butts","doi":"10.1017/nws.2023.4","DOIUrl":"https://doi.org/10.1017/nws.2023.4","url":null,"abstract":"Abstract When subjected to a sudden, unanticipated threat, human groups characteristically self-organize to identify the threat, determine potential responses, and act to reduce its impact. Central to this process is the challenge of coordinating information sharing and response activity within a disrupted environment. In this paper, we consider coordination in the context of responses to the 2001 World Trade Center (WTC) disaster. Using records of communications among 17 organizational units, we examine the mechanisms driving communication dynamics, with an emphasis on the emergence of coordinating roles. We employ relational event models (REMs) to identify the mechanisms shaping communications in each unit, finding a consistent pattern of behavior across units with very different characteristics. Using a simulation-based “knock-out” study, we also probe the importance of different mechanisms for hub formation. Our results suggest that, while preferential attachment and pre-disaster role structure generally contribute to the emergence of hub structure, temporally local conversational norms play a much larger role in the WTC case. We discuss broader implications for the role of microdynamics in driving macroscopic outcomes, and for the emergence of coordination in other settings.","PeriodicalId":51827,"journal":{"name":"Network Science","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135927288","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Segregated mobility patterns amplify neighborhood disparities in the spread of COVID-19 隔离的流动模式扩大了COVID-19传播中的社区差异

IF 1.7

Network Science Pub Date : 2023-04-17 DOI: 10.1017/nws.2023.6

András György, Thomas Marlow, B. Abrahao, K. Makovi

{"title":"Segregated mobility patterns amplify neighborhood disparities in the spread of COVID-19","authors":"András György, Thomas Marlow, B. Abrahao, K. Makovi","doi":"10.1017/nws.2023.6","DOIUrl":"https://doi.org/10.1017/nws.2023.6","url":null,"abstract":"\u0000 The global and uneven spread of COVID-19, mirrored at the local scale, reveals stark differences along racial and ethnic lines. We respond to the pressing need to understand these divergent outcomes via neighborhood level analysis of mobility and case count information. Using data from Chicago over 2020, we leverage a metapopulation Susceptible-Exposed-Infectious-Removed model to reconstruct and simulate the spread of SARS-CoV-2 at the ZIP Code level. We demonstrate that exposures are mostly contained within one’s own ZIP Code and demographic group. Building on this observation, we illustrate that we can understand epidemic progression using a composite metric combining the volume of mobility and the risk that each trip represents, while separately these factors fail to explain the observed heterogeneity in neighborhood level outcomes. Having established this result, we next uncover how group level differences in these factors give rise to disparities in case rates along racial and ethnic lines. Following this, we ask what-if questions to quantify how segregation impacts COVID-19 case rates via altering mobility patterns. We find that segregation in the mobility network has contributed to inequality in case rates across demographic groups.","PeriodicalId":51827,"journal":{"name":"Network Science","volume":"11 1","pages":"411-430"},"PeriodicalIF":1.7,"publicationDate":"2023-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"57044286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A network community detection method with integration of data from multiple layers and node attributes 一种结合多层数据和节点属性的网络社区检测方法

IF 1.7

Network Science Pub Date : 2023-03-07 DOI: 10.1017/nws.2023.2

H. Reittu, L. Leskelä, Tomi D. Räty

{"title":"A network community detection method with integration of data from multiple layers and node attributes","authors":"H. Reittu, L. Leskelä, Tomi D. Räty","doi":"10.1017/nws.2023.2","DOIUrl":"https://doi.org/10.1017/nws.2023.2","url":null,"abstract":"\u0000 Multilayer networks are in the focus of the current complex network study. In such networks, multiple types of links may exist as well as many attributes for nodes. To fully use multilayer—and other types of complex networks in applications, the merging of various data with topological information renders a powerful analysis. First, we suggest a simple way of representing network data in a data matrix where rows correspond to the nodes and columns correspond to the data items. The number of columns is allowed to be arbitrary, so that the data matrix can be easily expanded by adding columns. The data matrix can be chosen according to targets of the analysis and may vary a lot from case to case. Next, we partition the rows of the data matrix into communities using a method which allows maximal compression of the data matrix. For compressing a data matrix, we suggest to extend so-called regular decomposition method for non-square matrices. We illustrate our method for several types of data matrices, in particular, distance matrices, and matrices obtained by augmenting a distance matrix by a column of node degrees, or by concatenating several distance matrices corresponding to layers of a multilayer network. We illustrate our method with synthetic power-law graphs and two real networks: an Internet autonomous systems graph and a world airline graph. We compare the outputs of different community recovery methods on these graphs and discuss how incorporating node degrees as a separate column to the data matrix leads our method to identify community structures well-aligned with tiered hierarchical structures commonly encountered in complex scale-free networks.","PeriodicalId":51827,"journal":{"name":"Network Science","volume":"11 1","pages":"374-396"},"PeriodicalIF":1.7,"publicationDate":"2023-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"57044106","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0