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On the basis of modularity optimization, a genetic algorithm is proposed to detect community structure in networks by defining a local search operator. The local search operator emphasizes two features: one is that the connected nodes in a network should be located in the same community, while the other is “local selection” inspired by the mechanisms of efficient message delivery underlying the small‐world phenomenon. The results of community detection for some classic networks, such as Ucinet and Pajek networks, indicate that our algorithm achieves better community structure than other methodologies based on modularity optimization, such as the algorithms based on betweenness analysis, simulated annealing, or Tasgin and Bingol's genetic algorithm. © 2009 Wiley Periodicals, Inc. Complexity, 2010 相似文献
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我们考虑复杂网络社团结构的检测问题,即检测出那些具有高于平均密度的边所连接的节点的集合.本文我们利用模拟退火策略来极大化可表示为稳定效益函数的模量(modularity),并结合基于最短路径的$k$-均值迭代过程来对网络进行分区.该算法不仅能检测出社团,而且能够识别出在最短路径度量下,该社团中位于中心位置的节点.社团的最优数目可以在无需任何关于网络结构的先验信息下自动确定.对人工生成网络和真实世界中的网络的成功应用表明了算法的有效性. 相似文献
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For a given graph G, each partition of the vertices has a modularity score, with higher values indicating that the partition better captures community structure in G. The modularity q?(G) of the graph G is defined to be the maximum over all vertex partitions of the modularity score, and satisfies 0 ≤ q?(G)<1. Modularity is at the heart of the most popular algorithms for community detection. We investigate the behaviour of the modularity of the Erd?s‐Rényi random graph Gn,p with n vertices and edge‐probability p. Two key findings are that the modularity is 1+o(1) with high probability (whp) for np up to 1+o(1) and no further; and when np ≥ 1 and p is bounded below 1, it has order (np)?1/2 whp, in accord with a conjecture by Reichardt and Bornholdt in 2006. We also show that the modularity of a graph is robust to changes in a few edges, in contrast to the sensitivity of optimal vertex partitions. 相似文献
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非对称视角下技术创新网络社群结构涌现及其对双元创新的影响研究 总被引：3，自引：0，他引：3
针对介于全局网络与自中心网络间的社群现象及其网络结构的创新悖论,分析了不同层面网络社群结构的涌现特征,从组织间关系的非对称视角,探究网络社群动态变化对双元创新的差异性影响。利用高科技生物制药行业的合作与专利数据,使用快速压缩社群识别算法和多元回归模型进行实证检验。研究结果表明:宏观层面的全局网络存在显著“抱团”的多社群巨元组结构;中观层面的网络社群存在选择偏好的核心-边缘结构;微观层面社群组织动态的跨社群运动和成员流动二维变化加剧;社群动态的二维变化对突破式创新具有正向影响,与渐进式创新呈现倒U型关系;位置非对称性正向调节社群动态对双元创新的影响,技术非对称性的调节作用不显著。研究结论有助于揭示技术创新网络社群的合作创新模式,对提升组织创新能力,维持创新网络平稳运行具有重要意义。 相似文献
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本文以经济结构变化作为切入点对中国住房价格持续高涨现象进行分析,在构建理论分析模型的基础上,运用我国1999年至2011年省际面板数据进行了实证分析。研究结果表明:经济结构对商品房价格具有决定性的影响,长期来看,城乡收入分配结构、城镇化水平、工业化水平、以及财政分权水平决定了房价水平;短期来看,除了经济结构外,房价偏离长期均衡价格的水平决定了房价水平。 相似文献
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ROBB WILLER 《The Journal of mathematical sociology》2013,37(2):101-119
The question of what structures of relations between actors emerge in the evolution of social networks is of fundamental sociological interest. The present research proposes that processes of network evolution can be usefully conceptualized in terms of a network of networks, or “metanetwork,” wherein networks that are one link manipulation away from one another are connected. Moreover, the geography of metanetworks has real effects on the course of network evolution. Specifically, both equilibrium and non-equilibrium networks located in more desirable regions of the metanetwork are found to be more probable. These effects of metanetwork geography are illustrated by two dynamic network models: one in which actors pursue access to unique information through “structural holes,” and the other in which actors pursue access to valid information by minimizing path length. Finally, I discuss future directions for modeling network dynamics in terms of metanetworks. 相似文献
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Pawel M. Idziak 《Transactions of the American Mathematical Society》1997,349(3):903-934
For every finitely generated, congruence modular variety of finite type we find a finite family of finite rings such that the variety is finitely decidable if and only if is congruence permutable and residually small, all solvable congruences in finite algebras from are Abelian, each congruence above the centralizer of the monolith of a subdirectly irreducible algebra from is comparable with all congruences of , each homomorphic image of a subdirectly irreducible algebra with a non-Abelian monolith has a non-Abelian monolith, and, for each ring from , the variety of -modules is finitely decidable.
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带中心结构的社会网络是典型的现实网络类型.为了兼顾所有节点间关系信息,解决带中心结构的社会网络关系测度问题,选择Tabu搜索算法的块模型,提出综合测度节点角色和地位的指标.仿真实验进一步表明,提出的方法不仅将节点分"块",测度"块"间关系,同时提高网络节点评价维度的全面性、节点自带信息利用的充分性和对节点刻画的准确性,为社会网络关系测度问题研究提供一种工具,具有一定的现实意义. 相似文献
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Christian Meyer 《Mathematische Nachrichten》2003,259(1):66-73
We will examine the arithmetic of some of the members of a pencil of symmetric quintics in projective 4‐space. We will give evidence for the modularity of some of the exceptional members (even the non‐rigid ones) and give a proof in one rigid case. (© 2003 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim) 相似文献
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Ludomir Newelski 《Transactions of the American Mathematical Society》2002,354(3):925-943
We propose a model-theoretic framework for investigating profinite structures. We prove that in many cases small profinite structures interpret infinite groups. This corresponds to results of Hrushovski and Peterzil on interpreting groups in locally modular stable and o-minimal structures.
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关系型虚拟社区的社会网络特征研究 总被引：3，自引：0，他引：3
利用社会化网络软件建立的社会化网络网站,进一步扩充了虚拟社区中的人际关系的形式和内容.从人际关系的角度,我们把虚拟社区分为基于虚拟关系和基于现实关系两种类型.本文利用社会化网络分析方法,对这两种类型的虚拟社区进行量化分析,从网络密度、中心性等角度探讨了其网络结构的差异性. 相似文献
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Uwe Matzat 《Computational & Mathematical Organization Theory》2004,10(3):205-226
This paper analyzes two questions. First, under which conditions does a norm emerge in academic online groups that prescribes members to help others during group discussions? Second, what effects does such a norm, and other social conditions, have on the contributing behavior of researchers during online discussions? It is argued that the Coleman model (1990) on the emergence of norms points to an important condition that facilitates the realization of such a norm. According to the Coleman model (1990) a dense network among members of a group tends to strengthen a group norm. The paper makes a distinction between different kinds of academic online groups. The criterion of the distinction is the extent to which within the membership a highly integrated research community exists. An online group with a highly integrated research community is called to have a high degree of social embeddedness of its online communication in offline networks. It is hypothesized that a high degree of embeddedness has a number of effects. A higher degree of embeddedness leads to a stronger help-prescribing norm. The stronger the norm the more researchers send online answers to questions of their co-members during public online discussions. Furthermore, a high degree of embeddedness increases the answering behavior of researchers directly because it provides opportunities to gain reputation within the academic community through contributing to the discussion. The study makes use of data that consist of a combination of survey data and observed data of the communication behavior of researchers in about 50 international academic emailing lists. The results provide evidence for the expected effect of embeddedness on the strength of the norm and for the effect of embeddedness on the answering behavior of researchers. The strength of the help-prescribing norm indirectly influences the answering behavior. 相似文献
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In this article, we develop a simple model for the effect of gossip spread on social network structure. We define gossip as information passed between two individuals A and B about a third individual C which affects the strengths of all three relationships: it strengthens A‐B and weakens both B‐C and A‐C. We find, in both an analytic derivation and model simulations, that if gossip does not spread beyond simple triads, it destroys them but if gossip propagates through large dense clusters, it strengthens them. Additionally, our simulations show that the effect of gossip on network metrics (clustering coefficient, average‐path‐length, and sum‐of‐strengths) varies with network structure and average‐node‐degree. © 2010 Wiley Periodicals, Inc. Complexity 16: 39‐47, 2011 相似文献
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This paper studies the temporal communication patterns of online communities of developers and users of the open source Eclipse Java development environment. It measures the productivity of each community and seeks to identify correlations that exist between group communication characteristics and productivity attributes. The study uses the TeCFlow (Temporal Communication Flow) visualizer to create movie maps of the knowledge flow by analyzing the publicly accessible Eclipse developer mailing lists as an approximation of the social networks of developers and users. Thirty-three different Eclipse communities discussing development and use of components of Eclipse such as the Java Development Tools, the different platform components, the C/C++ Development Tools and the AspectJ extension have been analyzed over a period of six months. The temporal evolution of social network variables such as betweenness centrality, density, contribution index, and degree have been computed and plotted. Productivity of each development group is measured in terms of two indices, namely performance and creativity. Performance of a group is defined as the ratio of new bugs submitted compared with bugs fixed within the same period of time. Creativity is calculated as a function of new features proposed and implemented. Preliminary results indicate that there is a correlation between attributes of social networks such as density and betweenness centrality and group productivity measures in an open source development community. We also find a positive correlation between changes over time in betweenness centrality and creativity, and a negative correlation between changes in betweenness centrality and performance.This paper was tied for Best Paper, NAACSOS (North American Association for Computational Social and Organizational Science) Annual Conference 2005, June 26–28, Notre Dame.
Yared H. Kidane obtained a B.Sc. from Addis Ababa University, Ethiopia in Statistics and a M.Sc. in Information Technology specializing in engineering and management of information systems with honors from Royal Institute of Technology Stockholm, Sweden in June 2005. Yared completed his master’s thesis as an exchange student at MIT. He is currently working for Verizon Wireless as an analyst in the reporting and analysis section.
Peter A. Gloor is a research fellow both at the MIT Center for Coordination Science and the Center for Digital Strategies at Tuck at Dartmouth and chief scientist at iQuest Analytics. Previously, he was a partner with Deloitte and PwC. He obtained a Ph.D. in Computer Science from the University of Zurich in 1989, and was a Post-Doc at the MIT Lab for Computer Science. 相似文献
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This article investigates the impact of network structure on innovation efficiency by establishing a simulation model of innovation process in the context of innovation networks. The results indicate that short path lengths between vertices are conductive to high efficiency of explorative innovations, dense clusters are conductive to high efficiency of exploitative innovations, and high small‐worldness is conductive to high efficiency of the hybrid of these two innovations. Moreover, we discussed the reason of the results and give some suggestions to innovators and innovation policy makers. © 2014 Wiley Periodicals, Inc. Complexity 21: 111–122, 2015 相似文献
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Abstract Network analysis quantifies different structural properties of systems of interrelated parts using a single analytical framework. Many ecological phenomena have network‐like properties, such as the trophic relationships of food webs, geographic structure of metapopulations, and species interactions in communities. Therefore, our ability to understand and manage such systems may benefit from the use of network‐analysis techniques. But network analysis has not been applied extensively to ecological problems, and its suitability for ecological studies is uncertain. Here, we investigate the ability of network analysis to detect spatial patterns of species association in a tropical forest. We use three common graph‐theoretic measures of network structure to quantify the effect of understory tree size on the spatial association of understory species with trees in the canopy: the node degree distribution (NDD), characteristic path length (CPL), and clustering coefficient (CC). We compute the NDD, CPL, and CC for each of seven size classes of understory trees. For significance testing, we compare the observed values to frequency distributions of each statistic computed from randomized data. We find that the ability of network analysis to distinguish observed patterns from those representing randomized data strongly depends on which aspects of structure are investigated. Analysis of NDD finds no significant difference between random and observed networks. However, analysis of CPL and CC detected nonrandom patterns in three and one of the seven size classes, respectively. Network analysis is a very flexible approach that holds promise for ecological studies, but more research is needed to better understand its advantages and limitations. 相似文献
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针对社团结构发现算法仅考虑对象间相互关系的密集程度,忽视对象间属性特征差异的不足,提出考虑属性信息的复杂网络社团结构发现算法.算法引入属性特征相似度、基于属性特征相似度的有权网络、内聚度3个核心概念,迭代选取使内聚度指标上升最快的合并操作,自底向上实现社团聚集.由于考虑了属性信息,算法输出的社团结构具有更高准确度,更具应用价值. 相似文献
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Bonne J.H. Zijlstra 《The Journal of mathematical sociology》2017,41(4):185-192
In common models for dyadic network regression, the density and reciprocity parameters are dependent on each other. Here, the j1 and j2 models are introduced with a density parameter that represents the log odds of a single tie. Consequently, the density and reciprocity parameters are independent and the interpretation of both parameters more straightforward. Estimation procedures and simulation results for these new models are discussed as well as an illustrative example. 相似文献