Social Networks is an interdisciplinary and international quarterly. It provides a common forum for representatives of anthropology, sociology, history, social psychology, political science, human geography, biology, economics, communications science and other disciplines who share an interest in the study of the empirical structure of social relations and associations that may be expressed in network form. It publishes both theoretical and substantive papers. Critical reviews of major theoretical or methodological approaches using the notion of networks in the analysis of social behaviour are also included, as are reviews of recent books dealing with social networks and social structure.

Social Networks is an interdisciplinary and international quarterly journal. It serves as a common forum for representatives from various fields, including anthropology, sociology, history, social psychology, political science, human geography, biology, economics, and communication science, who share an interest in studying the empirical structure of social relations and associations that can be expressed in network form. The journal publishes both theoretical and substantive papers, as well as critical reviews of major theoretical or methodological approaches that utilize the concept of networks in analyzing social behavior. Additionally, it includes reviews of recent books related to social networks and social structure.

《Social Networks》是一本跨学科的国际季刊。它为人类学、社会学、历史、社会心理学、政治科学、人文地理学、生物学、经济学、传播科学等多个学科的代表提供了一个共同的论坛，这些学科的研究者都对社会关系和社会关联的实证结构感兴趣，这些结构可以用网络形式表达。期刊发表理论性和实质性的论文，同时也包括对使用网络概念分析社会行为的主要理论或方法论的批判性评审，以及对涉及社会网络和社会结构的近期书籍的评审。

Social Networks

Stephen P. Borgatti

Centrality and network flow

中心性和网络流

Tore Opsahl

Filip Agneessens

John Skvoretz

Node centrality in weighted networks: Generalizing degree and shortest paths

加权网络中的节点中心性：广义度与最短路径

A common but informal notion in social network analysis and other fields is the concept of a core/periphery structure. The intuitive conception entails a dense, cohesive core and a sparse, unconnected periphery. This paper seeks to formalize the intuitive notion of a core/periphery structure and suggests algorithms for detecting this structure, along with statistical tests for testing a priori hypotheses. Different models are presented for different kinds of graphs (directed and undirected, valued and nonvalued). In addition, the close relation of the continuous models developed to certain centrality measures is discussed.

Stephen P Borgatti

Martin G Everett

Models of core/periphery structures

核心/外围结构模型

We present a Multiple Membership Multiple Classification (MMMC) model for analysing variation in the performance of organizational sub-units embedded in a multilevel network. The model postulates that the performance of organizational sub-units varies across network levels defined in terms of: (i) direct relations between organizational sub-units; (ii) relations between organizations containing the sub-units, and (iii) cross-level relations between sub-units and organizations. We demonstrate the empirical merits of the model in an analysis of inter-hospital patient mobility within a regional community of health care organizations. In the empirical case study we develop, organizational sub-units are departments of emergency medicine (EDs) located within hospitals (organizations). Networks within and across levels are delineated in terms of patient transfer relations between EDs (lower-level, emergency transfers), hospitals (higher-level, elective transfers), and between EDs and hospitals (cross-level, non-emergency transfers). Our main analytical objective is to examine the association of these interdependent and partially nested levels of action with variation in waiting time among EDs – one of the most commonly adopted and accepted measures of ED performance. We find evidence that variation in ED waiting time is associated with various components of the multilevel network in which the EDs are embedded. Before allowing for various characteristics of EDs and the hospitals in which they are located, we find, for the null models, that most of the network variation is at the hospital level. After adding these characteristics to the model, we find that hospital capacity and ED uncertainty are significantly associated with ED waiting time. We also find that the overall variation in ED waiting time is reduced to less than a half of its estimated value from the null models, and that a greater share of the residual network variation for these models is at the ED level and cross level, rather than the hospital level. This suggests that the covariates explain some of the network variation, and shift the relative share of residual variation away from hospital networks. We discuss further extensions to the model for more general analyses of multilevel network dependencies in variables of interest for the lower level nodes of these social structures.

Mark Tranmer

Francesca Pallotti

Alessandro Lomi

The embeddedness of organizational performance: Multiple Membership Multiple Classification Models for the analysis of multilevel networks

组织绩效的嵌入性：多层次网络分析的多成员多分类模型

This paper examines organizational learning through a multilevel network lens. We assess how interpersonal knowledge transfer is sustained by the organizational structure of interunit work-flow ties and by the level of specialism of the connected units. To do this, we apply Multilevel Exponential Random Graph Models on data collected in a multiunit government institution in Italy. Results indicate that our approach allows simplifying and better understanding of organizational learning. Units are more likely to retain knowledge transfer ties within their boundaries. Unit boundary-spanning tends to occur only when knowledge transfer ties are sustained by hierarchical interunit work-flow ties.

Paola Zappa

Garry Robins

Organizational learning across multi-level networks

多层次网络中的组织学习

Nick Wuestenenk

Tom Nijs

Tobias H. Stark

Frank van Tubergen

Naomi Ellemers

The interplay of misperceptions and willingness to share opinions in full classroom networks: The case of opinions towards homosexuality

全班网络中误解与分享意见意愿的相互作用：以对同性恋的看法为例

Dmitry Gromov

Social balance-based centrality measure for directed signed networks

基于社会平衡的有向符号网络中心性度量

Shu-Mei Lai

Tso-Jung Yen

Ming-Yi Chang

Yang-chih Fu

Wei-Chung Liu

Predicting network members from partial contact records on social media: A machine learning approach

基于社交媒体部分联系记录预测网络成员：一种机器学习方法

Axel Browne

David Butts

Edgar Jaramillo-Rodriguez

Nidhi Parikh

Geoffrey Fairchild

Zach Needell

Cristian Poliziani

Tom Wenzel

Timothy C. Germann

Sara Del Valle

Corrigendum to “Evaluating disease surveillance strategies for early outbreak detection in contact networks with varying community structure” [Soc. Netw. 79 (2024) 122–132]

“评估疾病监测策略在具有不同社区结构的接触网络中早期疫情检测”的勘误 [《社会网络》79卷 (2024年) 122-132页]

Cristina Espinosa da Silva

Heather A. Pines

Thomas L. Patterson

Stephanie Brodine

Richard S. Garfein

Robert E. Booth

Eileen V. Pitpitan

The role of network communication in mediating the effect of a social network intervention on HIV seroconversion among people who inject drugs in Ukraine

网络通信在调节社会网络干预对乌克兰注射毒品人群艾滋病毒血清转化影响中的作用

Abbreviation	Soc. Networks.
Journal Impact	2.98
Quartiles(Global)	SOCIOLOGY(Q1)

ISSN	0378-8733, 1879-2111
h-index	114

Publication Information	Publisher: Elsevier B.V.，Publishing cycle: ，Journal Type: journal，Open Access Journals: No
Basic data	Year of publication: 1978，Proportion of original research papers: 100.00%，Self Citation Rate:10.30%， Gold OA Rate: 41.67%

Social Networks

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