The development of structure in random networks: an analysis of the effects of increasing network density on five measures of structure

The density of ingroup relations continues to be proposed as an indicator of structural cohesion. Network density is obviously a misleading indicator of structural cohesion when a group has subgroups; in such circumstances, the cohesion may be entirely internal to the subgroups. However, it is plausible that network density is a useful indicator of structural cohesion when it can be assumed that a group lacks subgroups. In order to analyze this possibility, I construct a set of random networks, increase the density of relations in these networks, and observe how the networks' structure develops in terms of five measures. The results show that low densities in large networks may be associated with more structural cohesion than higher densities in smaller networks; it is suggested that in field studies, attempts to control for network size will encounter problems of nonlinearity and heteroscedasticity. I conclude that network density is not a useful indicator of structure and that direct measurement of structure is to be preferred.     

Conditionally exponential random models for individual properties and network structures: Method and application

Exponential random models have been widely adopted as a general probabilistic framework for complex networks and recently extended to embrace broader statistical settings such as dynamic networks, valued networks or two-mode networks. Our aim is to provide a further step into the generalization of this class of models by considering sample spaces which involve both families of networks and nodal properties verifying combinatorial constraints. We propose a class of probabilistic models for the joint distribution of nodal properties (demographic and behavioral characteristics) and network structures (friendship and professional partnership). It results in a general and flexible modeling framework to account for homophily in social structures. We present a Bayesian estimation method based on the full characterization of their sample spaces by systems of linear constraints. This provides an exact simulation scheme to sample from the likelihood, based on linear programming techniques. After a detailed analysis of the proposed statistical methodology, we illustrate our approach with an empirical analysis of co-authorship of journal articles in the field of neuroscience between 2009 and 2013.     

Network brokerage and the perception of leadership

We renovate a classic experiment to define a research platform that provides data on network behavior and the causal effect of access to structural holes. Our hypothesis is that people are perceived to be leaders when they behave as network brokers, which is to say, when they coordinate information across structural holes. We focus on the perception of leadership to connect with the many field studies in which access to structural holes predicts success measures keyed to leadership. Our hypothesis is clearly supported. The broker-leader association we report is very similar in strength and form to broker-success associations reported in previous research. At the same time, it is also clear that people adapt to their randomly assigned network, re-shaping it to suit preferences that in some part emerge in team deliberations or outside the experiment. A modification to our hypothesis — at least for these small laboratory teams — is that monopoly brokerage is key to being cited as team leader. Leadership is ambiguous when multiple people are positioned to be brokers unless one person emerges by his or her network behavior as a monopoly broker. Our summary conclusion is that access to structural holes can be causal to the perception of leadership, a characteristic implicit in many success measures used to document the broker-success association.     

Using multiple network analytic tools for a single social network

A variety of data analytic network tools are used to study the structure of a social network where the properties of these tools rest on specific conceptualizations of some aspect of structure. Further, these tools have, in structural terms, ill-defined operationalizations and algorithmic details. As a result, they can lead to distinct characterizations of structure. The appropriate task in using multiple methods is not the use them all to see what they converge on, but to select the structural properties of critical interest and use the tools most appropriate for those properties.     

Some properties of structural equivalence measures derived from sociometric choice data

I discuss and illustrate the extent to which different relation measures and pattern similarity measures can be expected to generate different structural equivalence results. Measures of network relations and pattern similarity are reviewed to establish clear comparisons between structural equivalence measures. Using Monte Carlo sociometric choice data drawn from four strategically designed study populations, alternative relation and pattern similarity measures are combined in a factorial design generating six measures of structural equivalence within each study population. I report the magnitudes of differences between structural equivalence measures within populations, compared across populations. Three conclusions are drawn: (1) There is significant reliability across alternative measures. (2) This reliability increases with the clarity of boundaries between statuses in a study population. (3) The noticeable differences between structural equivalence measures that exist under conditions at all weaker than strong equivalence are principally a function of how relations are measured rather than how relation pattern similarities are measured. Two inferences are drawn for applied network analysis: (1) Structural equivalence should be computed from path distance measures of network relations (however normalized) rather than being computed directly from patterns of binary choice data. (2) Renewed methodological attention should shift from how we measure pattern similarity to how we measure relationships.     

法律洞的司法跨越——关系密切群体法律治理的社会网络分析

当法官(法律)面对村民及其关系密切群体时,对方无结构洞,而自己周边有法律洞,处于不利的网络位置。为此,法官(法律)采取将村长、习惯法和调解嵌入的策略,填补法律洞以提高结构自主性。当法官(法律)面对陌生人群体时,可利用对方存在结构洞以提高结构自主性,但这时的法官(法律)还未处于自己无法律洞而对方有结构洞的最佳网络位置。因此,中国法治最紧迫的任务是实现国家制定法与中国因素的有机融合以填补法律洞。     

Boundary maintenance in support networks

Most studies of social networks, whether they are viewed as the context of stressful experiences or of supportive interactions, assume fixed network boundaries. This assumption is necessary in order to analyze structural characteristics such as network density. Actual networks, however, change over time and across situations and the assumption of fixed boundaries is inappropriate for processual questions. Examination of such changes reveals limitations in the structural analysis of social networks and points to mechanisms and strategies by which network boundaries are drawn and redrawn.     

The structure of coalitional power under probabilistic voting procedures

We consider probabilistic voting procedures which map each feasible set of alternatives and each utility profile to a social choice lottery over the feasible set. It is shown that if we impose: (i) a probabilistic collective rationality condition known as regularity; (ii) probabilistic counterpart of Arrow's independence of irrelevant alternatives and citizens' sovereignty; (iii) a probabilistic positive association condition called monotonicity; then the coalitional power structure under a probabilistic voting procedure is characterized by weak random dictatorship. Received: 1 March 1999/Accepted: 21 May 2001     

Innovation as a structural interest: rethinking the impact of network position on innovation adoption

The act of adopting an innovation is argued to be a type of structural interest. The proposed conception of innovation as a structural interest describes how a potential adopter perceives utility in innovating as a function of his position in network(s) of relations with other potential adopters. Implications of the concept are in accord with diffusion research describing the linkage between social structure and innovation in terms of a potential adopter's social integration. The proposed concept avoids, however, three ambiguities in translating social integration into a structural concept stated in terms of network position. Moreover, it extends the scope of earlier work to suggest new connections between social structure and innovation.In order to make empirical implications explicit, hypotheses for a reanalysis of the classic Medical Innovation data are described. The proposed conception of innovation states the utility a doctor should perceive in prescribing a new drug as a function of his position in professional and social networks among other doctors in his community. The hypotheses predict when a doctor should begin prescribing a new drug and the relative importance of his personal characteristics versus network position as the determinant of when he begins prescribing the new drug.     

网络结构与权力分配:要素论的解释

中国的社会网研究很少关注网络结构与权力分配之间的关系,这恰是要素论的贡献。在介绍影响、社会关系、社会行动者等基本要素之后,本文分析了要素论的建模原理及多种结构条件,并简析其优势所在。要素论研究发现,权力的分配取决于行动者的偏好、信念、关系类型及诸多结构条件,因此,核心点未必有权。要素论根据网络结构预测权力的分配,这是其独特之处。该理论的其他优势有:坚持理论导向的实验研究,揭示了权力来源于排除机制,运用分析—组合法,可用于研究大型的、复杂的社会历史结构。本文最后讨论了要素论的未来方向,包括考虑到行动者的属性和结构的转换以及关系的要素论研究会加深对中国社会的认识等。     

The effect of spatial arrangement on judgments and errors in interpreting graphs

The spatial arrangement of social network data in graphs can influence viewers' perceptions of structural characteristics such as prominence, bridging and grouping. To study the extent of this effect, we conducted an experiment with 80 graduate students. Each student viewed three of five different spatial arrangements of the same network. We found that viewers' perceptions of structural features of the network changed as the spatial arrangement of the network changed.     

Jaccard-Spline index of structural proximity in contact networks

Network analysts are increasingly being called upon to apply their expertise to groups for which the only available or reliable data is a contact network. With no opportunity to gather additional data, the merits of such applications depend on empirical studies that validate the employment of structural constructs based on contact networks. Fortunately, we possess such studies in abundance. One of the strongest research traditions in social network analysis is the development of formal constructs that may be employed in analyses of networks. I suggest that greater insight into predictive success of network constructs may be acquired by addressing the following question: what features of the contact network in which a dyad is situated allow the prediction of other relations with an accuracy that validates the imputation of the latter given data on the former? In this article, I present findings on the structural contexts of dyads in contact networks and the relationship of these contexts with two fundamental forms of cohesive cognitive relations—accorded interpersonal influence and perceived interpersonal agreement. Based on these findings, I formalize a measure of structural proximity in contact networks with values that correspond to the conditional probabilities of these two forms of cohesive cognitive relations. The substantive settings of this analysis are policy groups with members who are embedded in contact structures based on regular interpersonal communication on policy issues and cognitive structures based on perceived interpersonal agreement and accorded interpersonal influence.     

Gender and Networks in a Local Voluntary-Sector Elite

Focusing on gender inequality in a local community elite, we investigate the role of gender in access to and participation in networks of nonprofit trustees in Louisville, Kentucky. We examine two types of network relations: participation in the network of overlapping board memberships (the structural network) and interpersonal ties of collegiality and friendship (the social network). Asking whether the gender hierarchy found in most private and public sector organizations is mirrored in this inner circle of trustees, with men occupying the most influential positions in the structural and social networks, we find some male advantage in the structural network. Men predominate in holding most board seats, occupying multiple board seats, and in having slightly greater network centrality. By contrast, women hold the edge in the social network, with slightly greater centrality and higher levels of social integration. Women's disadvantage in the structural network is at least partly counterbalanced by their prominence in the social network of trustees in Louisville. Results indicate that the local nonprofit sector includes a small number of women (but no people of color) in leadership roles.     

The evolution of structural resilience of global oil and gas resources trade network

This paper establishes anetwork resilience evaluation framework of the global oil and gas resourcetrade network in 2010, 2015 and 2020. The results are as follows: The links of the oil trade network present a gradually shrinking trend, and the gas tradenetwork presents a trend of close connection first and then reduced. In termsof network density, network centrality, network connectivity and network size, the structural resilience of the oil and gas resource trade network displays ashrinking trend, and the gas trade network is superior. Concerninginvulnerability and recovery, the resilience of the oil trade network issuperior to the natural gas trade network. In simulated attacks, the oil tradenetwork reveals a higher resilience towards intentional attacks, and the gastrade network shows a higher resilience towards random attacks. The Strait ofHormuz and the Strait of Malacca are critical chokepoints in the networks.