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Social Networks

(《社會(huì)網(wǎng)絡(luò)》)

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期刊簡(jiǎn)介

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.

The editorial criteria for acceptance will be based on the degree to which a paper makes a broad theoretical or methodological, and empirically relevant, contribution to the study of social networks. Acceptable papers may range from abstract, formal mathematical derivations to concrete, descriptive case studies of particular social networks. The editors are therefore particularly interested in papers that attempt to uncover the processes by which social networks emerge, evolve and have consequences for other aspects of behaviour. However, for reports of empirical research results, manuscripts must contain the following: a discussion of sampling, representation, and generalizability; a substantive foundation based on the social network literature; a consideration of social network processes; and feature meaningful data.

期刊影響力

CiteScore（引用分）：數(shù)值為5.7。CiteScore是Elsevier（愛思唯爾）基于 Scopus數(shù)據(jù)庫(kù)計(jì)算的指標(biāo)，能夠衡量期刊平均每篇文章在一定時(shí)間內(nèi)被引用的次數(shù)，從而反映期刊整體影響力和文章被關(guān)注程度。

Impact Factor（影響因子）：數(shù)值為2.4。IF由Clarivate Analytics（科睿唯安）基于Web of Science數(shù)據(jù)庫(kù)計(jì)算，計(jì)算方式為某期刊前兩年發(fā)表論文在統(tǒng)計(jì)年被引用總次數(shù)除以該期刊前兩年發(fā)表論文總數(shù)。IF是國(guó)際上常用評(píng)判期刊學(xué)術(shù)水平的指標(biāo)之一，體現(xiàn)期刊近期論文被引用的頻率和學(xué)術(shù)影響力。

Current Issue

Social Networks 為季刊，每年發(fā)布四期，最新一期(Volume 83，October 2025)共計(jì)15篇文章，詳情如下。

ARTICLES

# ARTICLE 1

Socio-cognitive networks between researchers: Investigating scientific dualities with the group-oriented relational hyperevent model

Andrea Fronzetti Colladon, Maurizio Naldi

Understanding why researchers cite certain works remains a key question in the study of scientific networks. Prior research has identified factors such as relevance, group cohesion, and source crediting. However, the interplay between cognitive and social dimensions in citation behavior – often conceptualized as a socio-cognitive network – is frequently overlooked, particularly regarding the intermediary steps that lead to a citation. Since a citation first requires a work to be published by a set of authors, we examine how the structure of coauthorship networks influences citation patterns. To investigate this relationship, we analyze the citation and collaboration behavior of Chilean astronomers from 2013 to 2015 using the Group-Oriented Relational Hyperevent Model, which allows us to study coauthorship and citation networks in a joint framework. Our findings suggest that when selecting which works to cite, authors favor recent research and maintain cognitive continuity across cited works. At the same time, we observe that coherent groups – closely connected coauthors – tend to be co-cited more frequently in subsequent publications, reinforcing the interdependence of collaboration and citation networks.

# ARTICLE 2

Embeddedness, status, and groups: Networks and employment in the American television production

Erez Aharon Marantz, Jeff Sachs, Emily Erikson

This paper analyzes how network communities condition the effects of embeddedness and status. Many economic fields are segmented into network communities that shape market activity. Using data on the hiring of 39,870 television producers from 1948 to 2010, we show that community membership moderates the effects of embeddedness and status. Embeddedness and status positively affect producers' employment by members of their communities, but negatively impact their employment by non-community members. These results contribute to the understanding of the operation of embeddedness and status in markets and to efforts to incorporate community-level dynamics into network analysis.

# ARTICLE 3

Overlapping social circles in historical elite career networks: Measuring accumulated social status with ‘k-circles’ and circle esteem in bipartite networks

Eugene T.Y. Ang, Prasanta Bhattacharya, Andrew E.B. Lim

By extending Breiger’s (1974) notion of the duality of persons and groups to biographical data, individuals and organisations can be linked through career overlaps, formalised as k-circles, a minimal members decomposition approach. This k-circle measure is used to identify key individuals and organisations in biographies of more than 30,000 Danish elites between 1910 and 2020. We compare the central circle based on CV data to an elite identified through affiliation networks, showing that k-circles identify career hubs rather than the meeting points of elites. We discuss how k-circles are associated with standard measures of centrality.

# ARTICLE 4

A comparison of top-coding strategies for aggregated relational data

Jody Clay-Warner, Hui Yi, Tenshi Kawashima, Jiacheng Li, Fred Hassan Konteh

Aggregated relational data are commonly used in conjunction with scale-up methods to measure network size. In this approach, the number of people respondents report knowing in subpopulations of known size are scaled-up to estimate the size of their personal network. Because this method is sensitive to reporting errors, researchers often top-code responses about subpopulations of known size, although there is no consensus on how to select the top-code value. Here, we compare several top-coding methods, including new approaches that utilize Dunbar’s number, using datasets collected from two aggregated relational data surveys, one from Shanghai and one from Kambia, Sierra Leone. We employ three metrics to evaluate the top-coding strategies: mean error rates in the estimation of the subpopulations of known size, error rate in estimation of the target population, and degree mean. We find that the top-coding strategies all perform equally well in the estimation of the subpopulations of known size in both datasets. The strategies based on Dunbar’s number, however, performed better than the other strategies in the estimation of the target population in Kambia. In addition, the Dunbar’s number approaches produced substantially smaller degree means in both datasets. We examine these findings wholistically and provide suggestions for how researchers should approach top-coding decisions. We ultimately conclude that there is not a one-size-fits-all solution for top-coding and that researchers should systematically examine key indicators from the data to determine if top-coding is necessary and, if so, what top-coding strategy is appropriate.

# ARTICLE 5

Bully-victim network perceptions of bullies, victims, and peer observers

Kyosuke Tanaka, Keqin Zhang, eremy Foote, Seungyoon Lee, Doran C. French

Bullying is a complex social construct, and informants (e.g., bullies, victims, and peer observers) may have differing perceptions about bully-victim relationships. This study examines how informant perspectives differ using network data obtained from 438 fifth-grade students (Mage = 11.19 years old, 46?% girls) in 13 Indonesian elementary school classrooms. Using a cross-informant framework, we investigated how self- and peer-reported bully-victim relationships overlapped as a function of the sex of bullies and victims, friendship ties, and relational schemas (i.e., mental network heuristics). Results from a multiplex exponential random graph model revealed significant agreement between self- and peer-reports. There was greater agreement when bully-victim relationships occurred between non-friends. When self- and peer-reports disagreed, peers identified more instances of boys engaging in bullying than girls, as well as more cross-sex than same-sex bully-victim relationships. Self-reports more often identified bully-victim relationships between friends than between non-friends. Post-hoc analyses revealed that bullies and their friends often had conflicting views of their friendship. Additionally, peers reported more victims per bully and fewer bullies per victim when compared to self-reports. These findings contribute to the understanding of the network structure of bully-victim perceptions and offer practical implications for identifying bully-victim relationships.

# ARTICLE 6

Explaining contact patterns in acquaintanceship networks: A new covariate-based model

Derick S. Baum

Aggregate relational data (ARD) on individuals’ ties to groups in a population offer valuable insights into the size of personal networks and the extent of segregation in contact with those groups. However, existing ARD models face two key limitations. First, they mask heterogeneity in network sizes across individuals who may differ markedly in relevant characteristics despite exhibiting similar response patterns on the ARD instrument. Second, although existing models can measure the overall level of segregation in contact with groups, they cannot reveal the determinants of segregation. To address these limitations, we introduce the Covariate Model, a regression-based framework that incorporates respondent covariates into analyses of ARD. We illustrate this model using ARD on contact with occupational categories. In addition to obtaining more substantively plausible network size estimates than existing approaches, the Covariate Model uncovers novel segregation patterns. For example, covariates — driven primarily by educational differences — account for a considerable portion of the segregation in contact with Higher Service occupations (e.g., lawyers and professors) but contribute little to explaining barriers to interaction with other occupational classes. By modeling the determinants of contact patterns in acquaintanceship networks, the Covariate Model extends the analytical reach of ARD and opens new avenues for research on social capital and segregation.

# ARTICLE 7

Double agency and co-evolution for two-mode networks, with an application to corporate interlocks and firms’ environmental performance

Tom A.B. Snijders, Beata ?opaciuk-Gonczaryk

Three extensions of the Stochastic Actor-oriented Model for two-mode networks are proposed. The first represents tie changes based on agency for both node sets. The second is a model for selection and influence in co-evolution of two two-mode networks, where the first is a membership network which serves to represent connections between groups making choices of activities in the second network. The third consists of new effects for categorical nodal covariates, representing the heterogeneity between nodes that often occurs in two-mode networks. As an illustration, selection and influence processes are studied in the co-evolution of the director interlock network of a set of 141 large European companies and the two-mode network of environmental policies of these companies, for the period from 2018 to 2022. Similarity between environmental policies is expressed in two ways: endorsing the same policy items, and correlation between the number of items endorsed. The findings show that declared pro-environmental practices spread through directorate interlocks and directors’ selection is based on peer referral.

# ARTICLE 8

Urban environmental stewardship networks: How organizations collaborate, share resources, and exchange knowledge within Baltimore, Maryland

Selena M. Livas, Dexter H. Locke, Nancy F. Sonti

Who are the groups stewarding the environment within local communities, where do they work, and who do they work with? The Stewardship Mapping and Assessment Project (STEW-MAP) survey has cataloged and mapped environmental stewardship groups in dozens of cities within the US and worldwide. The survey collects relational, network ties among respondents and their collaborators. In this study, we focus on the 2019 Baltimore, Maryland survey to better understand the relationships among environmental stewardship organizations across the city. We utilize exponential random graph models (ERGMs) to explore the factors that predict the formation of three distinct types of ties: collaboration, resource sharing, and knowledge sharing. The networks include 1,201 nodes with 2,884 total ties among them. Our results show that the network structure of each tie type is unique, but there is a shared tendency for degree distributions to be positively skewed, indicating the presence of many lower degree nodes. We also find that the main focus of these organizations and the organization type create substantial variation in their behavior; with some groups siloed, and others underutilized, one set of groups has managed to permeate all three networks: stormwater-focused groups. This study is the first to analyze this specific dataset and one of the few to use network models to analyze data collected through the STEW-MAP project. This work helps us understand the social forces shaping Baltimore’s stewardship network, while pointing to ways in which practitioners could potentially expand their reach. Overall, this work helps broaden our understanding of local environmental cooperation within a modern urban context.

# ARTICLE 9

Networks of inclusion: Using teams and technology to create diverse social capital

Sarah J. Gordon, Wayne E. Baker, Jose Uribe, Cassandra R. Chambers, Bruce A. Desmarais

This study of intraorganizational network dynamics develops a structural approach to the concept of inclusion in organizations. This approach is a complement to the definition of inclusion as a social-psychological response to experiences in a diverse social environment. We analyze networks of interaction over time in a large population of students and evaluate the extent to which two interventions—working in teams and using a social networking service (SNS)—grew and diversified their social capital. Using network data collected before and after 518 undergraduate students worked in 96 teams and participated in the SNS, we analyze the formation of new bridging social capital (ties between demographically dissimilar people) and new bonding social capital (ties between demographically similar people). Team membership had a large effect on social capital, creating positive bonding ties and bridging ties. But teams also created negative ties. The SNS facilitated tie formation but did not create negative ties. Together, the two interventions expanded networks and shifted the balance of ties in favor of bridging ties, producing a more structurally inclusive network. Our study demonstrates how intentional practices can be used to improve network inclusivity, as well as the value of viewing diversity and inclusion through the lens of intraorganizational network dynamics.

# ARTICLE 10

The Correspondence Analysis of two-mode networks revisited

Omar Lizardo

This paper reconsiders the status of Correspondence Analysis (CA) as a tool for analyzing two-mode networks, comparing it with the Bonacich dual centrality approach and revealing the mathematical linkages between them as eigenvector-based methods. While Bonacich centrality identifies core–periphery structures and is helpful for clustering nodes based on the criterion of similarity via structural equivalence, CA is best at detecting subsets of actors and events based on a generalized relational similarity criterion, thus coming closer to clustering via regular equivalence. Ultimately, both CA and Bonacich centrality prove to be valuable yet distinct strategies for the dual projection analysis of two-mode networks, highlighting the duality between actors and events.

# ARTICLE 11

Modeling the duality of content niches and user interactions on online social media platforms

Alvaro Uzaheta, Viviana Amati, Christoph Stadtfeld

Individuals use online social media platforms for social interaction and to create, consume and share creative content. Within large platforms, individuals’ interaction with content and the congregation of individuals sharing similar interests might have a dual relationship, leading to the emergence of focused content niches of specific individuals and types of content. These niches are smaller-scale social settings that may facilitate and structure interpersonal social interaction. This study introduces a novel two-step analytical framework to explore the influence of content niche affiliation on interaction patterns. In the first step, we employ Stochastic Block Models (SBMs) to analyze a two-mode network comprising content pieces and user-generated keywords assigned to them. This analysis uncovers distinct content niches where users can engage with one another. In the second step, We integrate these identified niches as independent variables within a Dynamic Network Actor Model (DyNAM) to investigate whether time-stamped user interaction dynamics are associated with these content niches. We illustrate the framework’s applicability through a case study of an online community catering to aspiring and professional designers, revealing the relationship between content niche affiliation and social interactions.

# ARTICLE 12

Who’s in your extended network? Analysing the size and homogeneity of acquaintanceship networks in the Netherlands

Beate V?lker, Bas Hofstra, Rense Corten, Frank van Tubergen

This study advances the understanding of the size and homogeneity of personal networks, focusing on extended networks that encompass both core discussion ties and the broader array of acquaintances. While previous research has primarily examined these dimensions within small, strong-tie networks, knowledge about extended networks remains limited. Using data from the Dutch Network Size Survey (2021), a representative survey of the Dutch adult population, this study provides novel insights into the size, gender, and educational homogeneity of extended networks, as well as individual variation across these dimensions. Employing the Network Scale-Up Method (NSUM) with an extensive set of scale-up items, we find a median extended network size of 446 and a mean size of 518. Substantial variation exists across individuals, with larger networks associated with being employed, having more household members, being younger, possessing greater resources (e.g., income, wealth), and attaining higher levels of education. Additionally, our findings reveal significant gender and educational segregation within extended networks. These results shed light on the structure of extended networks and highlight the social stratification of network size and homogeneity.

# ARTICLE 13

The duality of network ties and attributes

Annabell Schü?ler, Jan A. Fuhse

The article formulates an important extension of the concept of duality for network research: the duality of network ties and attributes. We transfer Breiger’s notion of the duality of cases and their attributes to network data to argue: dyads are defined by their attributes, including various kinds of relationship practices, individual traits, and combinations of traits. Conversely, the meaning of relationship practices is defined by the dyads displaying them, and by implication, by their other attributes. We illustrate the duality principle with an empirical study of sociometric nominations among 161 six-graders in eight German secondary school classes to examine: How do different kinds of ties – interpersonal relations and interest in collaborations in mathematics and physical education – relate to each other? What kinds of ties form between what kinds of school children? And how do one-sided nominations for friendship and sympathy differ from reciprocated ones? Since we do not expect monocausal relations, we conduct multiple correspondence analysis with directed ego-alter dyads as cases to explore these interrelations visually. In our analyses, school children want to collaborate with friends, and not with disliked peers. Affective ties like sympathy and friendships are chiefly same-gender and form around foci-of-activity like the neighborhood. Interest in collaborations in sports and mathematics is closely associated with interpersonal ties, but also with school grades and attributed capability in the respective subjects. Finally, one-sided nominations for friendship and sympathy indicate interpersonal ties that are weaker and less multiplex.

# ARTICLE 14

The cultural construction of personal relationships

Oscar Stuhler

Network analysis aspires to be “anticategorical,” yet its basic units—relationships—are, usually readily categorized entities with labels like “friendship,” “l(fā)ove,” or “patronage.” In, this way, a nontrivial cultural typification underlies the very building blocks of most network analyses. Despite work showing that a specific “type of tie” often stands in for quite heterogeneous empirical phenomena, this typification is seldom challenged in research practice. This article expands on recent efforts to more adequately theorize ties by further developing and arguing for the concept of relationship frames—cultural models that stabilize relational expectations. I suggest that such frames are rooted in regularities in the duality of dyad and content. Building on this idea, I develop a formal notion of frame ambiguity—the extent to which the actions and symbols designating a relationship index a variety of frames rather than just one. Putting these ideas to analytical use, I inductively identify relationship frames from the content of 1.2 million relationships between characters in fiction writing. I conclude with an exploratory investigation of some of the conditions under which ties in fiction writing display variation in frame ambiguity.

# ARTICLE 15

In the network of the conclave: Social connections and the making of a pope

Giuseppe Soda, Alessandro Iorio, Leonardo Rizzo

This study brings a network perspective to papal elections by mapping the relational architecture of the College of Cardinals. Using publicly available data sources, such as official Vatican directories and episcopal consecration records, we assemble a multiplex network that captures cardinals’ co-membership in various collegial bodies of the Vatican and their consecration ties. We then calculate structural metrics to capture three key mechanisms that we suggest have a crucial role in the dynamics of the conclave: status, mediation power, and coalition building. Our descriptive study—publicly released prior to the May 8, 2025 election of Pope Leo XIV—shows that Cardinal Robert F. Prevost, largely ignored by pundits, bookmakers, and AI models, held a uniquely advantageous position in the Vatican network, by virtue of being central in multiple respects. Thus, although being considered an underdog by many, the network perspective suggests that Cardinal Prevost was de facto one of the strongest “papabile.”

以上就是本期JCS 外刊吃瓜的全部?jī)?nèi)容啦

期刊/趣文/熱點(diǎn)/漫談

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JCS

《中國(guó)社會(huì)學(xué)學(xué)刊》（The Journal of Chinese Sociology）于2014年10月由中國(guó)社會(huì)科學(xué)院社會(huì)學(xué)研究所創(chuàng)辦。作為中國(guó)大陸第一本英文社會(huì)學(xué)學(xué)術(shù)期刊，JCS致力于為中國(guó)社會(huì)學(xué)者與國(guó)外同行的學(xué)術(shù)交流和合作打造國(guó)際一流的學(xué)術(shù)平臺(tái)。JCS由全球最大科技期刊出版集團(tuán)施普林格·自然(Springer Nature)出版發(fā)行，由國(guó)內(nèi)外頂尖社會(huì)學(xué)家組成強(qiáng)大編委會(huì)隊(duì)伍，采用雙向匿名評(píng)審方式和“開放獲取”(open access)出版模式。JCS已于2021年5月被ESCI收錄。2022年，JCS的CiteScore分值為2.0（Q2），在社科類別的262種期刊中排名第94位，位列同類期刊前36%。2025年JCS最新影響因子1.3，位列社會(huì)學(xué)領(lǐng)域期刊全球前53%（Q3）。

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