Network Science最新文献_第4页

Understanding collaboration patterns on funded research projects: A network analysis 理解资助研究项目的合作模式:网络分析

IF 1.7

Network Science Pub Date : 2022-11-23 DOI: 10.1017/nws.2022.33

Matthew Smith, Y. Sarabi, D. Christopoulos

引用次数: 1

Random networks grown by fusing edges via urns 随机网络通过urn融合边缘

IF 1.7

Network Science Pub Date : 2022-11-03 DOI: 10.1017/nws.2022.30

K. R. Bhutani, Ravi Kalpathy, H. Mahmoud

引用次数: 4

Network Science: 7th International Winter Conference, NetSci-X 2022, Porto, Portugal, February 8–11, 2022, Proceedings 网络科学:第七届国际冬季会议，NetSci-X 2022，波尔图，葡萄牙，2022年2月8-11日，会议录

IF 1.7

Network Science Pub Date : 2022-10-21 DOI: 10.1007/978-3-030-97240-0

Carlos Andre Reis Pinheiro

引用次数: 1

How teams adapt to exogenous shocks: Experimental evidence with node knockouts of central members 团队如何适应外部冲击：核心成员节点敲除的实验证据

IF 1.7

Network Science Pub Date : 2022-09-01 DOI: 10.1017/nws.2022.26

Jared F. Edgerton, S. Cranmer, V. Finomore

{"title":"How teams adapt to exogenous shocks: Experimental evidence with node knockouts of central members","authors":"Jared F. Edgerton, S. Cranmer, V. Finomore","doi":"10.1017/nws.2022.26","DOIUrl":"https://doi.org/10.1017/nws.2022.26","url":null,"abstract":"Abstract Researchers have found that although external attacks, exogenous shocks, and node knockouts can disrupt networked systems, they rarely lead to the system’s collapse. Although these processes are widely understood, most studies of how exogenous shocks affect networks rely on simulated or observational data. Thus, little is known about how groups of real individuals respond to external attacks. In this article, we employ an experimental design in which exogenous shocks, in the form of the unexpected removal of a teammate, are imposed on small teams of people who know each other. This allows us to causally identify the removed individual’s contribution to the team structure, the effect that an individual had on those they were connected, and the effect of the node knockout on the team. At the team level, we find that node knockouts decrease overall internal team communication. At the individual level, we find that node knockouts cause the remaining influential players to become more influential, while the remaining peripheral players become more isolated within their team. In addition, we also find that node knockouts may have a nominal influence on team performance. These findings shed light on how teams respond and adapt to node knockouts.","PeriodicalId":51827,"journal":{"name":"Network Science","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42460808","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

Connectivity-preserving distributed algorithms for removing links in directed networks 有向网络中去除链路的保连通分布式算法

IF 1.7

Network Science Pub Date : 2022-09-01 DOI: 10.1017/nws.2022.25

Azwirman Gusrialdi

{"title":"Connectivity-preserving distributed algorithms for removing links in directed networks","authors":"Azwirman Gusrialdi","doi":"10.1017/nws.2022.25","DOIUrl":"https://doi.org/10.1017/nws.2022.25","url":null,"abstract":"Abstract This article considers the link removal problem in a strongly connected directed network with the goal of minimizing the dominant eigenvalue of the network’s adjacency matrix while maintaining its strong connectivity. Due to the complexity of the problem, this article focuses on computing a suboptimal solution. Furthermore, it is assumed that the knowledge of the overall network topology is not available. This calls for distributed algorithms which rely solely on the local information available to each individual node and information exchange between each node and its neighbors. Two different strategies based on matrix perturbation analysis are presented, namely simultaneous and iterative link removal strategies. Key ingredients in implementing both strategies include novel distributed algorithms for estimating the dominant eigenvectors of an adjacency matrix and for verifying strong connectivity of a directed network under link removal. It is shown via numerical simulations on different type of networks that in general the iterative link removal strategy yields a better suboptimal solution. However, it comes at a price of higher communication cost in comparison to the simultaneous link removal strategy.","PeriodicalId":51827,"journal":{"name":"Network Science","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48193587","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

Strong and weak tie homophily in adolescent friendship networks: An analysis of same-race and same-gender ties. 青少年友谊网络中的强弱关系同质性:同种族和同性关系的分析。

IF 1.7

Network Science Pub Date : 2022-09-01 DOI: 10.1017/nws.2022.24

Cassie McMillan

引用次数: 1

NWS volume 10 issue 3 Cover and Front matter NWS第10卷第3期封面和封面

IF 1.7

Network Science Pub Date : 2022-09-01 DOI: 10.1017/nws.2022.28

引用次数: 0

Techniques for blocking the propagation of two simultaneous contagions over networks using a graph dynamical systems framework 利用图动态系统框架阻止两种同时传染在网络上传播的技术

IF 1.7

Network Science Pub Date : 2022-08-30 DOI: 10.1017/nws.2022.18

Henry L. Carscadden, C. Kuhlman, M. Marathe, Sujith Ravi, D. Rosenkrantz

{"title":"Techniques for blocking the propagation of two simultaneous contagions over networks using a graph dynamical systems framework","authors":"Henry L. Carscadden, C. Kuhlman, M. Marathe, Sujith Ravi, D. Rosenkrantz","doi":"10.1017/nws.2022.18","DOIUrl":"https://doi.org/10.1017/nws.2022.18","url":null,"abstract":"Abstract We consider the simultaneous propagation of two contagions over a social network. We assume a threshold model for the propagation of the two contagions and use the formal framework of discrete dynamical systems. In particular, we study an optimization problem where the goal is to minimize the total number of new infections subject to a budget constraint on the total number of available vaccinations for the contagions. While this problem has been considered in the literature for a single contagion, our work considers the simultaneous propagation of two contagions. This optimization problem is NP-hard. We present two main solution approaches for the problem, namely an integer linear programming (ILP) formulation to obtain optimal solutions and a heuristic based on a generalization of the set cover problem. We carry out a comprehensive experimental evaluation of our solution approaches using many real-world networks. The experimental results show that our heuristic algorithm produces solutions that are close to the optimal solution and runs several orders of magnitude faster than the ILP-based approach for obtaining optimal solutions. We also carry out sensitivity studies of our heuristic algorithm.","PeriodicalId":51827,"journal":{"name":"Network Science","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2022-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42880008","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

Generating weighted and thresholded gene coexpression networks using signed distance correlation. 使用符号距离相关生成加权和阈值基因共表达网络。

IF 1.7

Network Science Pub Date : 2022-06-01 Epub Date: 2022-06-16 DOI: 10.1017/nws.2022.13

Javier Pardo-Diaz, Philip S Poole, Mariano Beguerisse-Díaz, Charlotte M Deane, Gesine Reinert

{"title":"Generating weighted and thresholded gene coexpression networks using signed distance correlation.","authors":"Javier Pardo-Diaz, Philip S Poole, Mariano Beguerisse-Díaz, Charlotte M Deane, Gesine Reinert","doi":"10.1017/nws.2022.13","DOIUrl":"https://doi.org/10.1017/nws.2022.13","url":null,"abstract":"Even within well-studied organisms, many genes lack useful functional annotations. One way to generate such functional information is to infer biological relationships between genes or proteins, using a network of gene coexpression data that includes functional annotations. Signed distance correlation has proved useful for the construction of unweighted gene coexpression networks. However, transforming correlation values into unweighted networks may lead to a loss of important biological information related to the intensity of the correlation. Here we introduce a principled method to construct weighted gene coexpression networks using signed distance correlation. These networks contain weighted edges only between those pairs of genes whose correlation value is higher than a given threshold. We analyse data from different organisms and find that networks generated with our method based on signed distance correlation are more stable and capture more biological information compared to networks obtained from Pearson correlation. Moreover, we show that signed distance correlation networks capture more biological information than unweighted networks based on the same metric. While we use biological data sets to illustrate the method, the approach is general and can be used to construct networks in other domains. Code and data are available on https://github.com/javier-pardodiaz/sdcorGCN.","PeriodicalId":51827,"journal":{"name":"Network Science","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7613200/pdf/EMS145046.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"33520477","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

NWS volume 10 issue 2 Cover and Front matter NWS第10卷第2期封面和封面

IF 1.7

Network Science Pub Date : 2022-06-01 DOI: 10.1017/nws.2022.21

引用次数: 0