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NWS volume 8 issue 3 Cover and Front matter 国家气象局第8卷第3期封面和封面事项
IF 1.7 Q2 SOCIAL SCIENCES, INTERDISCIPLINARY Pub Date : 2020-09-01 DOI: 10.1017/nws.2020.29
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引用次数: 0
Where you are, what you want, and what you can do: The role of master statuses, personality traits, and social cognition in shaping ego network size, structure, and composition 你在哪里,你想要什么,你能做什么:主体性地位、人格特质和社会认知在塑造自我网络规模、结构和组成中的作用
IF 1.7 Q2 SOCIAL SCIENCES, INTERDISCIPLINARY Pub Date : 2020-09-01 DOI: 10.1017/nws.2020.6
Matthew E. Brashears, Laura Aufderheide Brashears, Nicolas L. Harder
Abstract Ego networks are thought to be influenced by the opportunities provided to associate with others given by our master statuses (e.g., race or sex), by the preferences individuals possess for interaction given our personality traits (e.g., extroverted or neurotic), and by the capacity to manage interactions on an ongoing basis given our cognitive ability to recall network information. However, prior research has been unable to examine all three classes of predictors concurrently. We rectify this deficiency in the literature by using a novel dataset of nearly 1000 respondents collected using controlled laboratory designs; using this dataset, we can simultaneously examine the impact of master statuses, personality traits, and social cognitive competencies on ego network size, structure (i.e., density), and composition (i.e., diversity). We find that all classes of predictors influence our ego networks, though in different ways, and point to new avenues for research into human sociability.
自我网络被认为受到以下因素的影响:由我们的主导地位(例如,种族或性别)提供的与他人交往的机会;由我们的人格特征(例如,外向或神经质)提供的个人对互动的偏好;以及由我们回忆网络信息的认知能力提供的持续管理互动的能力。然而,先前的研究无法同时检查所有三类预测因子。我们通过使用使用控制实验室设计收集的近1000名受访者的新数据集来纠正文献中的这一缺陷;使用这个数据集,我们可以同时检查主人地位、人格特征和社会认知能力对自我网络规模、结构(即密度)和组成(即多样性)的影响。我们发现,所有类型的预测因素都会以不同的方式影响我们的自我网络,并为研究人类社交能力指明了新的途径。
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引用次数: 3
NWS volume 8 issue 3 Cover and Back matter 美国国家气象局第8卷第3期封面和封底
IF 1.7 Q2 SOCIAL SCIENCES, INTERDISCIPLINARY Pub Date : 2020-09-01 DOI: 10.1017/nws.2020.30
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引用次数: 0
Social capital across the life course: Accumulation, diminution, or segregation? 贯穿一生的社会资本:积累、减少还是隔离?
IF 1.7 Q2 SOCIAL SCIENCES, INTERDISCIPLINARY Pub Date : 2020-08-06 DOI: 10.1017/nws.2020.26
Beate Volker
Abstract This study examines changes in individual social capital during adult life within a 19-year period. Social capital theory and life course theory are combined, and it is argued that changes in social networks do not necessarily go together with changes in social capital: while personal networks are known to decline in size with age, social capital can be expected to accumulate, in particular for those who had a better starting position and therefore more resources to share. Panel data from the survey of the social networks of the Dutch (SSND) (1999–2018) at four points of measurement are employed to inquire into this argument. Social capital is measured by the position generator instrument, and three indicators, that is, resource extensity, mean prestige access, and resource range are analyzed. Results of fixed effect models show that, on average, people maintain access to social capital, and that men and higher educated gain social capital through their life as opposed to women and lower educated. Implications for the understanding of the reproduction of social inequality are discussed. The paper concludes with a reflection upon the value of ego-centered network analysis in the era of big data and data science.
摘要本研究考察了19年内成人生活中个人社会资本的变化。社会资本理论和生命历程理论相结合,有人认为,社会网络的变化不一定与社会资本的变化同时发生:虽然众所周知,个人网络的规模会随着年龄的增长而下降,但社会资本可以积累,特别是对于那些有更好起点的人,因此可以分享更多资源。采用荷兰社会网络调查(SSND)(1999-2008)的四个测量点的面板数据来探究这一论点。利用位置生成器工具对社会资本进行度量,分析了资源广度、平均声望获取和资源范围三个指标。固定效应模型的结果表明,平均而言,人们能够获得社会资本,与女性和受教育程度较低的人相比,男性和受过高等教育的人一生都能获得社会资本。讨论了对理解社会不平等再生产的启示。文章最后对以自我为中心的网络分析在大数据和数据科学时代的价值进行了反思。
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引用次数: 40
Collaborative production networks among unequal actors 不平等行为者之间的协作生产网络
IF 1.7 Q2 SOCIAL SCIENCES, INTERDISCIPLINARY Pub Date : 2020-07-03 DOI: 10.1017/nws.2020.23
Manuel Muñoz-Herrera, J. Dijkstra, A. Flache, R. Wittek
Abstract We develop a model of strategic network formation of collaborations to analyze the consequences of an understudied but consequential form of heterogeneity: differences between actors in the form of their production functions. We also address how this interacts with resource heterogeneity, as a way to measure the impact actors have as potential partners on a collaborative project. Some actors (e.g., start-up firms) may exhibit increasing returns to their investment into collaboration projects, while others (e.g., established firms) may face decreasing returns. Our model provides insights into how actor heterogeneity can help explain well-observed collaboration patterns. We show that if there is a direct relation between increasing returns and resources, start-ups exclude mature firms and networks become segregated by types of production function, portraying dominant group architectures. On the other hand, if there is an inverse relation between increasing returns and resources, networks portray core-periphery architectures, where the mature firms form a core and start-ups with low-resources link to them.
摘要我们开发了一个合作的战略网络形成模型,以分析一种研究不足但后果严重的异质性形式的后果:行动者之间在生产职能形式上的差异。我们还讨论了这与资源异质性的相互作用,以此来衡量参与者作为合作项目的潜在合作伙伴所产生的影响。一些参与者(如初创公司)对合作项目的投资回报可能会增加,而其他参与者(如老牌公司)的回报可能会减少。我们的模型提供了参与者异质性如何帮助解释观察良好的协作模式的见解。我们发现,如果增加的回报和资源之间存在直接关系,初创企业将成熟企业排除在外,网络将按生产职能类型划分,从而描绘出主导的集团架构。另一方面,如果增加的回报和资源之间存在反比关系,那么网络描绘了核心-外围架构,成熟的公司形成核心,低资源的初创企业与之相连。
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引用次数: 1
NWS volume 8 issue S1 Cover and Back matter NWS第8卷第S1期封面和封底
IF 1.7 Q2 SOCIAL SCIENCES, INTERDISCIPLINARY Pub Date : 2020-07-01 DOI: 10.1017/nws.2020.28
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引用次数: 0
Introduction to the special issue on COMPLEX NETWORKS 2018 COMPLEX NETWORKS 2018特刊简介
IF 1.7 Q2 SOCIAL SCIENCES, INTERDISCIPLINARY Pub Date : 2020-07-01 DOI: 10.1017/nws.2020.22
H. Cherifi, Luis Mateus Rocha, S. Wasserman
We are extremely pleased to present this special issue of Network Science which contains a collec-tion of extended papers from the Seventh International Conference on Complex Networks & their Applications (COMPLEX NETWORKS 2018). Initiated in 2011, the conference series has grown to become one of the major international events in network science. Every year, it brings together researchers from a wide variety of scientific backgrounds ranging from finance and economics, medicine and neuroscience, biology and earth sciences, sociology and political science, computer science, physics, and many others in order to review the current state of the field and formu-late new directions. The great diversity of the participants allows for cross-fertilization between fundamental issues and innovative applications.
我们非常高兴地推出这期《网络科学》特刊,其中收录了第七届复杂网络及其应用国际会议(2018年复杂网络)的扩展论文集。该系列会议于2011年启动,现已发展成为网络科学领域的主要国际活动之一。每年,它都会汇集来自金融和经济学、医学和神经科学、生物学和地球科学、社会学和政治学、计算机科学、物理学等各种科学背景的研究人员,以回顾该领域的现状并形成新的方向。参与者的多样性使得基本问题和创新应用之间能够相互促进。
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引用次数: 0
NWS volume 8 issue S1 Cover and Front matter NWS第8卷第S1期封面和封面
IF 1.7 Q2 SOCIAL SCIENCES, INTERDISCIPLINARY Pub Date : 2020-07-01 DOI: 10.1017/nws.2020.27
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引用次数: 0
Faster MCMC for Gaussian latent position network models 用于高斯潜在位置网络模型的更快MCMC
IF 1.7 Q2 SOCIAL SCIENCES, INTERDISCIPLINARY Pub Date : 2020-06-13 DOI: 10.1017/nws.2022.1
Neil A. Spencer, B. Junker, T. Sweet
Abstract Latent position network models are a versatile tool in network science; applications include clustering entities, controlling for causal confounders, and defining priors over unobserved graphs. Estimating each node’s latent position is typically framed as a Bayesian inference problem, with Metropolis within Gibbs being the most popular tool for approximating the posterior distribution. However, it is well-known that Metropolis within Gibbs is inefficient for large networks; the acceptance ratios are expensive to compute, and the resultant posterior draws are highly correlated. In this article, we propose an alternative Markov chain Monte Carlo strategy—defined using a combination of split Hamiltonian Monte Carlo and Firefly Monte Carlo—that leverages the posterior distribution’s functional form for more efficient posterior computation. We demonstrate that these strategies outperform Metropolis within Gibbs and other algorithms on synthetic networks, as well as on real information-sharing networks of teachers and staff in a school district.
摘要潜在位置网络模型是网络科学中的一种通用工具;应用程序包括对实体进行聚类,控制因果混杂因素,以及在未观察到的图上定义先验。估计每个节点的潜在位置通常被定义为贝叶斯推理问题,吉布斯中的Metropolis是最流行的近似后验分布的工具。然而,众所周知,Gibbs内部的Metropolis对于大型网络来说效率低下;接受率的计算是昂贵的,并且得到的后验图是高度相关的。在这篇文章中,我们提出了一种替代的马尔可夫链蒙特卡罗策略——使用分裂哈密顿蒙特卡罗和萤火虫蒙特卡罗的组合定义——它利用后验分布的函数形式进行更有效的后验计算。我们证明,在合成网络以及学区教师和教职员工的真实信息共享网络上,这些策略优于Gibbs中的Metropolis和其他算法。
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引用次数: 4
Assessing the stability of egocentric networks over time using the digital participant-aided sociogram tool Network Canvas. 使用数字参与者辅助社交工具网络画布评估自我中心网络随时间的稳定性。
IF 1.7 Q2 SOCIAL SCIENCES, INTERDISCIPLINARY Pub Date : 2020-06-01 Epub Date: 2019-11-04 DOI: 10.1017/nws.2019.27
Bernie Hogan, Patrick Janulis, Gregory Lee Phillips, Joshua Melville, Brian Mustanski, Noshir Contractor, Michelle Birkett

This paper examines the stability of egocentric networks as reported over time using a novel touchscreen-based participant-aided sociogram. Past work has noted the instability of nominated network alters, with a large proportion leaving and reappearing between interview observations. To explain this instability of networks over time, researchers often look to structural embeddedness, namely the notion that alters are connected to other alters within egocentric networks. Recent research has also asked whether the interview situation itself may play a role in conditioning respondents to what might be the appropriate size and shape of a social network, and thereby which alters ought to be nominated or not. We report on change in these networks across three waves and assess whether this change appears to be the result of natural churn in the network or whether changes might be the result of factors in the interview itself, particularly anchoring and motivated underreporting. Our results indicate little change in average network size across waves, particularly for indirect tie nominations. Slight, significant changes were noted between waves one and two particularly among those with the largest networks. Almost no significant differences were observed between waves two and three, either in terms of network size, composition, or density. Data come from three waves of a Chicago-based panel study of young men who have sex with men.

本文使用一种新颖的基于触摸屏的参与者辅助社交图来研究自我中心网络的稳定性。过去的工作已经注意到被提名的网络改变者的不稳定性,在采访观察之间有很大比例的离开和重新出现。为了解释这种网络随时间的不稳定性,研究人员经常关注结构嵌入性,即在以自我为中心的网络中,改变者与其他改变者联系在一起的概念。最近的研究还提出了这样一个问题:面试情境本身是否会影响受访者对社交网络的适当大小和形状的判断,从而决定哪些变化应该被提名。我们报告了这些网络中的变化,并评估这种变化是网络中自然流失的结果,还是面谈本身因素的结果,特别是锚定和动机性低报。我们的研究结果表明,跨波的平均网络规模变化不大,特别是对于间接领带提名。在第一波和第二波之间发现了轻微的、显著的变化,尤其是那些拥有最大神经网络的人。在第二波和第三波之间,无论是在网络大小、组成还是密度方面,几乎没有观察到显著的差异。数据来自芝加哥一项针对男男性行为的年轻男性的三波小组研究。
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引用次数: 19
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Network Science
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