合作出版物多层网络的结构

Q1 Mathematics
Ghislain Romaric Meleu, Paulin Yonta Melatagia
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引用次数: 0

摘要

利用科学论文的标题,我们建立了涉及研究的实体的多层网络,即:作者、实验室和机构。我们分析了从HAL档案中提取的数据构建的网络的一些特性,发现每一层的网络都是一个幂律分布的小世界网络。为了模拟这种共同出版网络,我们提出了一种多层网络生成模型,该模型基于每一层的派系形成以及每个新节点与更高层的隶属关系。该集团是由使用优先连接选择的新节点和现有节点构建的。我们还表明,生成层的度分布遵循幂律。从我们模型的模拟中,我们表明生成的多层网络再现了共同出版网络的研究特性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The structure of co-publications multilayer network
Using the headers of scientific papers, we have built multilayer networks of entities involved in research namely: authors, laboratories, and institutions. We have analyzed some properties of such networks built from data extracted from the HAL archives and found that the network at each layer is a small-world network with power law distribution. In order to simulate such co-publication network, we propose a multilayer network generation model based on the formation of cliques at each layer and the affiliation of each new node to the higher layers. The clique is built from new and existing nodes selected using preferential attachment. We also show that, the degree distribution of generated layers follows a power law. From the simulations of our model, we show that the generated multilayer networks reproduce the studied properties of co-publication networks.
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来源期刊
Computational Social Networks
Computational Social Networks Mathematics-Modeling and Simulation
自引率
0.00%
发文量
0
审稿时长
13 weeks
期刊介绍: Computational Social Networks showcases refereed papers dealing with all mathematical, computational and applied aspects of social computing. The objective of this journal is to advance and promote the theoretical foundation, mathematical aspects, and applications of social computing. Submissions are welcome which focus on common principles, algorithms and tools that govern network structures/topologies, network functionalities, security and privacy, network behaviors, information diffusions and influence, social recommendation systems which are applicable to all types of social networks and social media. Topics include (but are not limited to) the following: -Social network design and architecture -Mathematical modeling and analysis -Real-world complex networks -Information retrieval in social contexts, political analysts -Network structure analysis -Network dynamics optimization -Complex network robustness and vulnerability -Information diffusion models and analysis -Security and privacy -Searching in complex networks -Efficient algorithms -Network behaviors -Trust and reputation -Social Influence -Social Recommendation -Social media analysis -Big data analysis on online social networks This journal publishes rigorously refereed papers dealing with all mathematical, computational and applied aspects of social computing. The journal also includes reviews of appropriate books as special issues on hot topics.
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