共查询到19条相似文献，搜索用时 156 毫秒
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节点对,指网络中一条联系及其两端节点的组合。作为信息网络中底层的联系组件,节点对表征最基础的信道,但却难以被直接测度。本文尝试引入删除法,构建节点对的间接测度,并给出分别测量网络整体节点数量（信息存量）和联系权重（信息流量）损失的LN和LS指数,用于挖掘无向网络中的关键节点对。h指数研究科研合作网络的实例显示,删除法挖掘出了该网络中具有组织作用、具有桥梁作用或具有相似结构对等性的各类关键节点对。基于删除法的信息网络间接测度方法,有望促成信息网络联系组件测度研究的新视域。图7。表2。参考文献26。 相似文献
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科研合作网络的知识扩散机理研究 总被引：1，自引：1，他引：0
知识扩散是知识生产过程中的核心环节,对知识继承和知识创新具有重要作用。本文结合知识在科研合作网络中的流动特征,引入复杂网络理论,构建知识扩散模型,模拟知识在科研合作网络中的扩散过程。考虑不同个体的知识自我增长以及知识吸收能力,采用网络平均知识水平、知识扩散速率、知识均衡程度等作为衡量知识扩散效果的评价指标,探究不同合作网络结构、知识遗传继承和知识变异重组与知识扩散的动态关系。研究显示:知识在合作网络中的知识水平、扩散速率、分布均衡程度很大程度上取决于网络拓扑结构的动态变化,网络的随机化程度越大,知识扩散的速度越快,知识的分布越均匀;合作网络的规模越小,专家高知识溢出效应越显著,越能促进知识的有效扩散;知识继承吸收和知识自我创新对知识扩散的影响在某一时刻可达到最佳均衡状态。研究合作网络中各影响因素对知识扩散的震荡作用,有利于形成更稳健的合作模式,发挥科研合作的最大效能。图9。表1。参考文献22。 相似文献
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[目的/意义]合理预测科研领域的潜在合作关系有助于优化资源配置,提升科研产出效率。从科研网络出发的潜在合作预测研究日益增长,需要系统总结。[方法/过程]在CNKI和Web of Science中检索并筛选出基于科研网络的潜在合作关系预测方法的研究,从年发文量、期刊分布对目标文献集进行统计分析。使用内容分析法,梳理出预测潜在合作关系的一般流程,描述步骤中的方法。[结果/结论]潜在合作关系预测一般流程为网络构建、特征提取与表示、合作预测和预测结果评价,其中构建的网络可分为同质网络、异质网络和二分网络,特征提取和表示可分为节点内容特征和网络结构特征,合作预测的方法主要有基于相似性的方法和基于机器学习的方法,预测结果评价的指标为AUC、Precision和Ranking Score;现有方法的局限性启示了未来潜在合作关系预测的发展方向。 相似文献
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[目的/意义]提出和构建网络舆情观点团簇演化等级,以描述网络舆情受众的群体性观点的状态随时间与事态变化的演化程度,对于网络舆情导控与精准引导具有重要的理论及实践意义。[方法/过程]基于LDA与CNN神经网络构建网络舆情观点团簇演化等级测度模型,并以"翟天临知网事件"为实验对象,验证演化等级这一指标的有效性。[结果/结论]网络舆情观点团簇演化等级能够很好地体现网络热点事件群体观点状态的演化,在展现3个维度的属性数值同时也能反映观点团簇较前一时间节点状态的演化程度,提出的观点团簇演化等级测度结果精准地体现事件观点的各个演化高峰,为有关部门对网络舆情群体观点的靶向引导提供新的指导方向。 相似文献
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文章对社会网络用户关系研究相关文献进行梳理和总结,对社会网络用户关系性质、用户关系网络形成相关理论进行阐述,然后总结关系网络测度相关指标和方法,探究网络中节点影响力的测度以及网络结构特征和演化规律,最后总结研究应用领域并展望未来研究方向。 相似文献
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为改变以往研究局限于从学科或地域交叉单一测度探究该跨度对科研协作知识交流影响的做法,本文融合分析学科交叉和地域交叉两个测度对科研协作知识流动元网络特征形成的复杂影响过程。先构建起科研协作知识流动元网络,并设置节点、子群、全网各维度特征分析的指标体系;然后分别根据计算出来的各指标值分析得到元网络特征;再分别从地域交叉和学科交叉两个测度分析得到这两个子网对应的在节点、子群、全网各维度的特征;最后建立起地域交叉和学科交叉子网与科研协作知识流动元网络特征之间的联系,得到学科交叉、地域交叉在科研协作知识流动元网络特征形成演化过程中的作用机理。 相似文献
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基于语义的社会网络关联路径评价及其应用 总被引：1，自引：0，他引：1
传统社会网络中节点和边是同质的,仅能包含社会组织的结构信息。将本体理论与社会网络分析理论相结合,使得网络的节点和边都具有特定的语义,这种网络称作语义社会网络。本文研究了运用本体描述语言OWL表示语义社会网络的方法;提出了语义社会网络中关联路径的概念和评价方法,并用于发现网络中的重要节点和重要的连接关系(包括隐含的间接关系)。对一个科研合作网络实例的研究,验证了语义社会网络表示方法的有效性。应用基于关联路径的方法对科研合作网络中的重要节点和重要隐含关系进行了分析,并对分析结果进行了评价,证明基于语义的方法可以有效地发现网络中的重要关系和重要节点。 相似文献
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作者科研合作网络模型与实证研究 总被引：1，自引：1，他引：1
基于科研论丈作者合作方式，建立一个作者科研合作网络模型。通过理论分析和仿真验证，网络模型节点的度分布（作者合作人数）符合幂率分布，该网络是一种无尺度网络模型。为了说明作者合作网络模型的有效性，对2001年1月至2006年12月期间发表在“图书情报工作》期刊上的科研论文进行统计，建立作者合作网络。对作者合作网络进行数据分析，结果与网络模型结论一致，因此该模型可以很好地描述作者合作网络的演化过程。 相似文献
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This paper proposes a new node centrality measurement index (c-index) and its derivative indexes (iterative c-index and cg-index) to measure the collaboration competence of a node in a weighted network. We prove that c-index observe the power law distribution in the weighted scale-free network. A case study of a very large scientific collaboration network indicates that the indexes proposed in this paper are different from other common centrality measures (degree centrality, betweenness centrality, closeness centrality, eigenvector centrality and node strength) and other h-type indexes (lobby-index, w-lobby index and h-degree). The c-index and its derivative indexes proposed in this paper comprehensively utilize the amount of nodes’ neighbors, link strengths and centrality information of neighbor nodes to measure the centrality of a node, composing a new unique centrality measure for collaborative competency. 相似文献
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How does the collaboration network of researchers coalesce around a scientific topic? What sort of social restructuring occurs as a new field develops? Previous empirical explorations of these questions have examined the evolution of co-authorship networks associated with several fields of science, each noting a characteristic shift in network structure as fields develop. Historically, however, such studies have tended to rely on manually annotated datasets and therefore only consider a handful of disciplines, calling into question the universality of the observed structural signature. To overcome this limitation and test the robustness of this phenomenon, we use a comprehensive dataset of over 189,000 scientific articles and develop a framework for partitioning articles and their authors into coherent, semantically related groups representing scientific fields of varying size and specificity. We then use the resulting population of fields to study the structure of evolving co-authorship networks. Consistent with earlier findings, we observe a global topological transition as the co-authorship networks coalesce from a disjointed aggregate into a dense giant connected component that dominates the network. We validate these results using a separate, complimentary corpus of scientific articles, and, overall, we find that the previously reported characteristic structural evolution of a scientific field's associated co-authorship network is robust across a large number of scientific fields of varying size, scope, and specificity. Additionally, the framework developed in this study may be used in other scientometric contexts in order to extend studies to compare across a larger range of scientific disciplines. 相似文献
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Convexity in a network (graph) has been recently defined as a property of each of its subgraphs to include all shortest paths between the nodes of that subgraph. It can be measured on the scale [0, 1] with 1 being assigned to fully convex networks. The largest convex component of a graph that emerges after the removal of the least number of edges is called a convex skeleton. It is basically a tree of cliques, which has been shown to have many interesting features. In this article the notions of convexity and convex skeletons in the context of scientific collaboration networks are discussed. More specifically, we analyze the co-authorship networks of Slovenian researchers in computer science, physics, sociology, mathematics, and economics and extract convex skeletons from them. We then compare these convex skeletons with the residual graphs (remainders) in terms of collaboration frequency distributions by various parameters such as the publication year and type, co-authors’ birth year, status, gender, discipline, etc. We also show the top-ranked scientists by four basic centrality measures as calculated on the original networks and their skeletons and conclude that convex skeletons may help detect influential scholars that are hardly identifiable in the original collaboration network. As their inherent feature, convex skeletons retain the properties of collaboration networks. These include high-level structural properties but also the fact that the same authors are highlighted by centrality measures. Moreover, the most important ties and thus the most important collaborations are retained in the skeletons. 相似文献
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[目的/意义]基于科学数据构建合作网络,并与传统出版物合作网络进行比较,从网络分析层面解读两个合作网络的差异,为科学数据管理工作提供借鉴。[方法/过程]以ClinicalTrials.gov网站的临床科学数据库为例,利用爬虫抓取该网站上传统论文题录信息以及临床试验信息的元数据并分别构建合作网络,通过复杂网络分析比较试验合作机构网络与论文合作机构网络之间的异同。[结果/结论]基于科学数据集和论文数据集的元数据构建的合作网络,与仅从论文数据集中提取元数据构建的网络相比,前者能够展现更丰富准确的合作信息,从而揭示科学数据管理和开放共享的重要性。 相似文献
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在系统调研跨地域科研协作现状基础上,本研究提出跨地域科研协作模式分析框架,以信息搜寻与信息检索融合（IS&R）等为测试主题,构建跨地域科研协作网络;计算无向加权科研协作网络节点中心性,发现各主题研究热点国家、城市和机构;模拟有向加权科研协作网络连接强度,描绘科研协作关系中知识流动方向;识别科研协作过程中节点角色,发掘城市科研协作主流模式;通过QAP分析,测度地理距离对节点间科研协作强度的影响,剖析节点科研实力与节点间科研协作强度的相关关系;借助演化分析,厘清科研协作网络发展历程及节点角色迁移情况。结果显示,上述主题在跨地域科研协作过程中既存在共性的节点分布、网络连接和扩展模式,又表现出一定的学科差异。图5。表11。参考文献23。 相似文献
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我国科研机构合作网络知识扩散研究——以“生物多样性”研究为例 总被引：1，自引：0，他引：1
通过对“生物多样性”研究高产机构所构成的合作网络进行社会网络分析,揭示科研机构合作网络知识扩散规律,剖析我国当前科研合作网络知识交流、扩散的特点。认为科研合作网络已成为科研领域的常态化事物,科研合作网络的结构对知识扩散具有重要要影响,因此,有必要全面探索其自身发展演变的规律,以促进科学知识的交流与扩散,同时也为我国科研政策的发展提供支持。 相似文献
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顾东蕾 《中华医学图书馆杂志》2008,(6):7-10
药物基因组学是一门年轻的学科领域。该领域内相关科学研究工作者之间形成的科研合作关系网络,也具有类似许多大型合作关系网络数据库所具有的无尺度网络特性,其非连通合作网络内部具有较大连通组群的聚类特性和小世界特征等相关性质。 相似文献
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We analyze the advent and development of eight scientific fields from their inception to maturity and map the evolution of their networks of collaboration over time, measured in terms of co-authorship of scientific papers. We show that as a field develops it undergoes a topological transition in its collaboration structure between a small disconnected graph to a much larger network where a giant connected component of collaboration appears. As a result, the number of edges and nodes in the largest component undergoes a transition between a small fraction of the total to a majority of all occurrences. These results relate to many qualitative observations of the evolution of technology and discussions of the “structure of scientific revolutions”. We analyze this qualitative change in network topology in terms of several quantitative graph theoretical measures, such as density, diameter, and relative size of the network's largest component.To analyze examples of scientific discovery we built databases of scientific publications based on keyword and citation searches, for eight fields, spanning experimental and theoretical science, across areas as diverse as physics, biomedical sciences, and materials science. Each of the databases was vetted by field experts and is the result of a bibliometric search constructed to maximize coverage, while minimizing the occurrence of spurious records. In this way we built databases of publications and authors for superstring theory, cosmic strings and other topological defects, cosmological inflation, carbon nanotubes, quantum computing and computation, prions and scrapie, and H5N1 influenza. We also built a database for a classical example of “pathological” science, namely cold fusion. All these fields also vary in size and in their temporal patterns of development, with some showing explosive growth from an original identifiable discovery (e.g. carbon nanotubes) while others are characterized by a slow process of development (e.g. quantum computers and computation).We show that regardless of the detailed nature of their developmental paths, the process of scientific discovery and the rearrangement of the collaboration structure of emergent fields is characterized by a number of universal features, suggesting that the process of discovery and initial formation of a scientific field, characterized by the moments of discovery, invention and subsequent transition into “normal science” may be understood in general terms, as a process of cognitive and social unification out of many initially separate efforts. Pathological fields, seemingly, never undergo this transition, despite hundreds of publications and the involvement of many authors. 相似文献