<abstract xmlns="http://www.w3.org/1999/xhtml">Hairball buster (HB) (also called node-neighbor centrality or NNC) is an approach to graph analytic triage that uses simple calculations and visualization to quickly understand and compare graphs. Rather than displaying highly interconnected graphs as ‘hairballs’ that are difficult to understand, HB provides a simple standard visual representation of a graph and its metrics, combining a monotonically decreasing curve of node metrics with indicators of each node’s neighbors’ metrics. The HB visual is canonical, in the sense that it provides a standard output for each node-link graph. It helps analysts quickly identify areas for further investigation, and also allows for easy comparison between graphs of different data sets. The calculations required for creating an HB display is order <italic>M</italic> plus <italic>N</italic> log <italic>N</italic>, where <italic>N</italic> is the number of nodes and <italic>M</italic> is the number of edges. This paper includes examples of the HB approach applied to four real-world data sets. It also compares HB to similar visual approaches such as degree histograms, adjacency matrices, blockmodeling, and force-based layout techniques. HB presents greater information density than other algorithms at lower or equal calculation cost, efficiently presenting information in a single display that is not available in any other single display.</abstract>

Hairball Buster: A Graph Triage Method for Viewing and Comparing Graphs

<abstract xmlns="http://www.w3.org/1999/xhtml">In order to understand scientists’ incentives to form collaborative relations, we have conducted a study looking into academically relevant resources, which scientists contribute into collaborations with others. The data we describe in this paper are an egocentric dataset assembled by coding originally qualitative material. It is 40 multiplex ego networks containing data on individual attributes (such as gender, scientific degree), collaboration ties (including alter–alter ties), and resource flows. Resources are coded using a developed inventory of 25 types of academically relevant resources egos and alters contribute into their collaborations. We share the data with the research community with the hopes of enriching knowledge and tools for studying sociological and behavioral aspects of science as a social process.</abstract>

Academic Collaboration via Resource Contributions: An Egocentric Dataset

<abstract xmlns="http://www.w3.org/1999/xhtml">Organizations have leeway in how much they employ their network relations to the benefit of their clients. When do they do so more rather than less? Relying on research on trust and knowledge absorption, the authors suggest that providers’ network relations generate better outcomes for their clients when these relations are concentrated in a limited, exclusive set of partners. The authors argue that providers’ relational exclusivity benefits clients because it facilitates the awareness and use of partners’ complementary client service capabilities. An analysis of a regional network of patient referrals among 110 hospitals supported this argument. The study highlights the role of interorganizational partnership networks in activating client service capabilities and stimulates further inquiry into providers’ network features that benefit the users of their services.</abstract>

Clients’ outcomes from providers’ networks: the role of relational exclusivity and complementary capabilities

<abstract xmlns="http://www.w3.org/1999/xhtml">In this paper, we consider whether brokerage in an intra-organizational communication network and type of work role interact to predict individual performance in a professional organization. The independent–interdependent nature of work roles is considered a key factor in structural contingency theory, but is yet to be studied in relation to brokerage. We propose that a brokerage position has a joint effect on performance along with work role in a study of organization-wide communication network in an architectural firm with 65 employees. Our analysis suggests an association between brokerage and role-prescribed performance for individuals in both interdependent and independent types of work roles. Our findings also suggest that interdependent roles requiring broad, organization-wide collaboration, and communication with others, brokerage is positively associated with the performance prescribed by the role, but for independent roles, wherein collaboration and communication are somewhat limited by the formal role, brokerage has far less of an effect. Our findings contribute to brokerage theory by comparing how brokerage affects performance in two distinct work roles by illustrating how the benefits of brokerage seem more restricted to those in interdependent work roles. The contribution of this paper is to suggest the independent–interdependent nature of work role as a boundary condition for brokerage.</abstract>

The contingent effect of work roles on brokerage in professional organizations

<abstract xmlns="http://www.w3.org/1999/xhtml">This paper is the written text underlying the keynote presentation at the Sunbelt XXXVIII in Utrecht, 2018. It presents a neo-structural approach to social processes in the organizational society and the usefulness of the analyses of multilevel networks to understand how we navigate these processes and are made aware of them when we face cooperation dilemmas. Empirical illustrations look at how multilevel networks and relational infrastructures are useful to research a process such as coopetitive learning in science, business and government. A conclusion focuses on the role of multilevel relational infrastructures in institutional entrepreneurship, social change and politics, as well as on our responsibility to develop our knowledge of these social processes and multilevel relational infrastructures as open science.</abstract>

Embarked on social processes (the rivers) in dynamic and multilevel networks (the boats)

<abstract xmlns="http://www.w3.org/1999/xhtml">In which social worlds does gender homophily operate more strongly – offline or online? To address this question, the following two aspects must be considered. First, people currently use many types of online communication media. Second, to examine the homophily effects exclusively, it is necessary to control for other network formation mechanisms such as ‘foci’ and ‘triadic closure.’ For this study, I conducted a mixed-method research in a high school in rural Japan. I asked students about who they interacted with face-to-face (F2F), through instant messenger (IM), and social networking services (SNS) and then analyzed the social networks using exponential random graph models (ERGMs). Subsequently, I conducted semi-structured interviews to uncover the practices and social contexts of each communication media and explain the results of the quantitative analysis. The results showed that SNS was more gender heterogeneous than offline. In the IM network, a small gender homophily effect was initially observed. However, three months later, its strength decreased to almost the same as that in the SNS networks. From the qualitative research, some key mechanisms producing the difference in gender homophily are specified, such as precedence of F2F communication to IM interaction, independence of SNS communication from F2F, recommending functions, and hobby homophily. Overall, this study implies that considering offline or online alone may cause misunderstanding regarding homophily in organizations because the observed strength of homophily effects depends on whether the space is examined offline or online, what kind of media is examined, and when the online social network data are collected.</abstract>

Comparing Gender Homophily among the Multilayer Media Social Networks of Face-to-Face, Instant Messenger and Social Networking Services: A Case Study of a High School Classroom

<abstract xmlns="http://www.w3.org/1999/xhtml">The book “Conducting Personal Network Research” is a conceptual and methodological introduction to the structural study of personal networks. It is part of a series of recent monographs that have begun to systematize the knowledge generated in this area in recent decades (Crossley et al., 2015; McCarty et al., 2019; Perry et al., 2018). In this case, the authors have dedicated a large part of their career to the empirical investigation of the interpersonal relationships, interaction contexts, and social integration processes of immigrants, along with other groups in vulnerable situations. With this publication, all this experience is now reflected in a clear and comprehensive introductory text. This book explains how to integrate relational data collection and analysis with survey research. It systematically presents the strategies to estimate the size of personal networks. Finally, it describes how to fit statistical analysis to relational data, including regression models, multi-level models, and longitudinal models.</abstract>

Commentary: How to do personal network surveys: from name generators to statistical modeling

<abstract xmlns="http://www.w3.org/1999/xhtml">The current study modeled formal and informal communication networks of an integrated project delivery (IPD) team and examined the interplay between the two networks. The IPD format as an alternative method of building construction relies on its multiple stakeholders’ equal and active collaboration. Analyses of both endogenous and exogenous network variables found very distinctive tie formation dynamics between the formal and informal communication networks. While both networks were rather decentralized, a preferred structure for facilitating collaboration in IPD teams, reciprocal communication was identified only in formal (i.e., project-related information exchange), not in informal (i.e., social conversations) networks in valued exponential random graph modeling (VERGM). Ethnic heterophily, also a preferred structure for the IPD collaboration, was significant for formal, but not for informal communication networks. A small number of female members (4 out of 26) were more participating in formal, but less in informal conversations compared to males. Team members from designer and contractor organizations were active in project-related information exchange, but not as much in social conversations compared to the owner’s representatives. While a multiplexity effect was identified between formal and informal communication networks in VERGM, MR-QAP regressions revealed the cyclicality of each network significantly predicted the other type of communication frequency above and beyond its own structural configuration.</abstract>

Communication networks of an integrated project delivery team for construction: relationships between formal and informal communication networks

<abstract xmlns="http://www.w3.org/1999/xhtml">The GROW Social Network datasets were compiled as part of a 3-year community-based family-based pediatric obesity prevention intervention (<italic>N</italic> = 610). The datasets include (i) multiplex edges between adult study participants at four timepoints (baseline, 3, 12, and 36 mon), and (ii) multiplex edges within small intervention-only subgroups (30 groups of approximately 10 adult intervention participants) and a previously validated self-report measure of perceived cohesion at three timepoints (3, 6, and 12 wk). Actor attributes are richly characterized in a linkable dataset.</abstract>

The ‘GROW Social Network’ datasets

<abstract xmlns="http://www.w3.org/1999/xhtml">Coronavirus disease of 2019 (COVID-19)’s devastating effects on the physical and mental health of the public are unlike previous medical crises, in part because of people’s collective access to communication technologies. Unfortunately, a clear understanding of the diffusion of health information on social media is lacking, which has a potentially negative impact on the effectiveness of emergency communication. This study applied social network analysis approaches to examine patterns of #COVID19 information flow on Twitter. A total of 1,404,496 publicly available tweets from 946,940 U.S. users were retrieved and analyzed. Particular attention was paid to the structures of retweet and mention networks and identification of influential users: information sources, disseminators, and brokers. Overall, COVID-19 information was not transmitted efficiently. Findings pointed to the importance of fostering connections between clusters to promote the diffusion in both networks. Lots of localized clusters limited the spread of timely information, causing difficulty in establishing any momentum in shaping urgent public actions. Rather than health and communication professionals, there was dominant involvement of non-professional users responsible for major COVID-19 information generation and dissemination, suggesting a lack of credibility and accuracy in the information. Inadequate influence of health officials and government agencies in brokering information contributed to concerns about the spread of dis/misinformation to the public. Significant differences in the type of influential users existed across roles and across networks. Conceptual and practical implications for emergency communication strategies are discussed.</abstract>

COVID-19 Health Communication Networks on Twitter: Identifying Sources, Disseminators, and Brokers

<abstract xmlns="http://www.w3.org/1999/xhtml">This picture, produced by Julien Brailly et al. (2016) and David Schoch (2020), visualizes multilevel networks of individuals and organizations.</abstract>

Visualizing Multilevel Networks for the Analysis of Superposed Levels of Collective Agency

AHEAD OF PRINT

Volume 44 (2024): Issue 1 (January 2024)

Volume 43 (2023): Issue 1 (January 2023)

Volume 42 (2022): Issue 1 (January 2022)

Volume 41 (2021): Issue 1 (January 2021)

Volume 40 (2020): Issue 1 (January 2020)

Volume 39 (2019): Issue 1 (January 2019)

Volume 38 (2018): Issue 1 (January 2018)

Volume 37 (2017): Issue 1-2 (January 2017)

Volume 36 (2016): Issue 1 (January 2016)

Connections

Connections publishes original empirical, theoretical, and methodological articles, as well as critical reviews dealing with applications of social network analysis. From volume 2018 the journal is published in a continous format.  The research spans many disciplines and domains including: Anthropology, Sociology, Psychology, Communication, Economics, Organizational Behavior, Knowledge Management, Marketing, Social Psychology, Mathematics, Public Health, Medicine, Computer Science, and Policy.  As an official journal of the International Network for Social Network Analysis, the emphasis of the publication is to reflect the ever-growing and continually expanding community of scholars using network analytic techniques. Connections also provides an outlet for sharing news about social network concepts and techniques and new tools for research.  Rejection rate: 60%  Open Access Policy  This journal provides immediate open access to its content under the Creative Commons CC BY 4.0 license on the principle that making research freely available to the public supports a greater global exchange of knowledge. Under the Creative Commons CC BY 4.0 license users are free to share (copy and redistribute the material in any medium or format) and adapt the work (remix, transform, and build upon the material for any purpose, even commercially) if the contribution was properly attributed and all of the changes indicated.  ABOUT SOCIETY  International Network for Social Network Analysis is the professional association for researchers interested in social network analysis. The association is a non-profit organization incorporated in the state of Delaware and founded by Barry Wellman in 1977.  INSNA was founded on the premise that the behavior and lives of social entities are affected by their position in the overall social structure. By examining the etiology and consequences of structural forms overall, of the location of entities within these structures, and of the formation and dynamics of ties that make up these structures, INSNA hopes to learn about the parts of behavior that are uniquely social.  Archiving  Sciendo archives the contents of this journal in Portico - digital long-term preservation service of scholarly books, journals and collections.  Plagiarism Policy  The editorial board is participating in a growing community of Similarity Check System's users in order to ensure that the content published is original and trustworthy. Similarity Check is a medium that allows for comprehensive manuscripts screening, aimed to eliminate plagiarism and provide a high standard and quality peer-review process.