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Organised Sessions

List of Accepted Organised Sessions

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Paris Wicker, Rachel Smith, Trevion Henderson, Michael Brown

 

Achieving equity in postsecondary education remains a global challenge and goal for college and universities worldwide. Whether the focus is college access and affordability, academic achievement, or quality of educational experiences, colleges and universities are seeking solutions to eliminate educational disparities that exist due to inequitable treatment based on immigration status, (dis)abilities, gender, race or caste, ethnicity, religion, or sexual orientation, among other factors. The purpose of this session is to highlight research that utilizes social network analysis to expose the structural mechanisms and processes that contribute to inequitable experiences and outcomes in postsecondary education, as well as opportunities where SNA might mitigate inequity. As the field of higher education continues to see an increase of Social Network Analysis in educational research, how has SNA provided additional context to the persistent inequities that plague higher education? Furthermore, what are the future possibilities for SNA to advance equity based research, policy, and practice? Session presentations will explore these questions, including empirical, theoretical, and conceptual perspectives, with the opportunity for attendees to engage in thoughtful discussion.

 

Federico Bianchi, Filip Agneessens, Andreas Flache, Károly Takács

 

Bridging micro- and macro-social levels of analysis is pivotal to both social network research and agent-based modelling (ABM), which has recently stimulated fruitful exchanges between the two fields. Recent developments in statistical modelling of longitudinal network data have brought up further discussions on the use of simulations in social network research. ABMs can explain network dynamics and macro-level outcomes through micro-level mechanisms. Unlike in the early days, the network component of an ABM can be calibrated with empirical data, which allows ABM modellers to move beyond the use of abstract networks. Moreover, ABM can be used as a complementary tool to increase generalizability of statistical analysis of network data. This session invites contributions that attempt to explain the emergence or evolution of social networks by linking individuals’ behaviour to social network dynamics through ABMs in studying e.g., processes of social selection, social influence, diffusion, opinion polarization, social conflicts or cooperation. Particularly — but not exclusively — welcome are contributions bridging theoretical ABM, empirical data, and statistical models of network-generating processes (e.g., ERGM, SAOM).

 

Charlie Joyez

 

Economics is fundamentally the study of interconnectedness: from market transactions between producers and consumers, to the structure of Global Supply Chains or the intertwined financial flows across banks, multiple actors are interrelated in any economic relationship. We know that Network Analysis is the proper tool to study the pattern of actor’s interactions, especially when we believe them not to be random as is the case for economic structures, the organization of production processes, or trade choices.
 
In this session we welcome research detailing the network structures of economic relationships and their evolution in a world that is increasingly interconnected through goods and capital flows. We will also particularly welcome papers that focus on the economic consequences of changing network structure or individual position into a network (e.g. gaining centrality) highlighting the benefit of network analysis to understand economic dynamics better.
 
Both theoretical and empirical research are welcome, with a particular (but not restricted) interest in papers focusing on the network foundation of the resilience of an economic or financial system to match the “Networks and Resilience“ theme of Sunbelt 2024.

Nikolitsa Grigoropoulou, Betina Hollstein

 

One of the major promises of “big data” was the ability to understand how social networks emerge, operate, and shape human behavior on a much larger scale than previously possible. Researchers have used large-scale network data to generate new insights on topics as varied as network evolution (Kossinets and Watts 2006), well-being (Jaidka et al. 2020), and political misinformation (Guess, Nyhan, and Reifler 2020), among many others. But researchers have become increasingly cognizant of the limits of “big data” analyses, which may include sampling bias in the data, confounds in the algorithms needed to uncover patterns, and weak construct validity (boyd and Crawford 2012; Lazer et al. 2014). An important response has been to address the limits of the data themselves by employing mixed- or multi-methods approaches that capitalize on the strengths of traditional social science methods, such as surveys, experiments, or various qualitative methods (Bail et al. 2020; Gilbert and Karahalios 2009; Grigoropoulou and Small 2022; Scharkow et al. 2020).
 
This organized session aims to host paper presentations on research in social networks that combine different types of data and methods. Critical reviews discussing specific methodological problems in large-scale network data and how they can be addressed with field research are also welcome.
 

Ian McCulloh, Ryan Wisnesky

 

A satellite conference on innovative approaches to social network data extraction, movement, and integration enabled by formal mathematical methods.
 
We invite researchers and practitioners to participate in a Satellite Conference dedicated to exploring cutting-edge methodologies in the integration, merging, and discovery of social network data at scale. This conference will provide a platform to delve into the transformative potential of relational calculus, category theory, and formal methods in the realm of social network data analysis.
 
As the digital era ushers in an unprecedented volume of social network data, the need for advanced techniques to efficiently process and derive insights from this wealth of information has never been more critical. We encourage contributions that showcase novel applications of relational algebra, relational calculus, category theory, and formal methods, emphasizing their ability to address challenges related to data integration, data merging, and the discovery of hidden patterns within social networks.
 
Topics of interest include, but are not limited to:
 
• Innovative data modeling approaches using relational calculus and category theory.
 
• Formal methods for ensuring data quality and integrity in large-scale social network datasets.
 
• Techniques for merging disparate social network data sources.
 
• Scalable algorithms for uncovering valuable insights within social networks.
 
• Case studies and real-world applications demonstrating the effectiveness of these methods.
 
This Satellite Conference offers an exceptional opportunity for researchers to share their insights, methodologies, and discoveries in the rapidly evolving field of social network data analysis. Join us in exploring the potential of these advanced techniques to revolutionize the way we integrate, merge, and extract knowledge from social network data. We look forward to your contributions and participation in this stimulating conference.
 

Jennifer Watling Neal

 

This organized session focuses on applications of social network analysis to understand the role of peer relationships in child and adolescent development and well-being. Children and adolescents spend a substantial portion of their time with peers, and their peer relationships can shape, and can be shaped by, their attitudes and behaviors. The session welcomes papers that make empirical, methodological and/or theoretical contributions to understandings of social networks in child and adolescent development and well-being, including (but not limited to) papers on:
 
(1) Peer selection and influence processes in childhood and adolescence
 
(2) Associations between structural features of child and adolescent social networks and psychosocial outcomes
 
(3) Contextual factors associated with child and adolescent social networks (e.g., teaching practices, behavioral norms, school organization), and innovations in modeling multi-level networks capturing context
 
(4) Advances in the measurement and analysis of child and adolescent social networks
 
Papers that focus on a range of developmental periods (i.e., early childhood, middle childhood, early adolescence) and types of peer relationships (e.g., friendships, play, bullying dynamics) are welcome.
 

Alejandro Ciordia, David Tindall, Mario Diani

 

Over the past three decades, the network perspective has become an increasingly common tool for analyzing various facets of collective action, social movements, and related phenomena. Network analyses have proven to be a powerful and versatile approach for enhancing our collective understanding of the dynamics surrounding activism, social protests, and contentious politics, whether examining the factors leading to mobilization, the interaction structures that emerge during collective action, or the consequences of collective action. This organized session invites contributions that span the spectrum of theoretical, substantive, and methodological aspects of collective action networks. We welcome conceptual and theoretically-informed empirical contributions that employ diverse methodological traditions (quantitative, qualitative, or mixed methods) and analytical designs (e.g., socio-centric vs. ego-centric, one-mode vs. multimodal, etc.). Analyses featured in this session may focus on different types of actors (e.g., individuals, organizations, institutions, etc.) or entities (e.g., claims, events, action forms, etc.) and consider any kind of relevant relationships, such as collaboration, conflict, co-presence, and beyond.

 

Roy Barnes, Joshua Murray

 

This session highlights the study of the role of social networks in consolidating the dominant position of business and economic elites. Applicants are invited to submit papers that use social network analysis at either local, national or transnational level. We’re particularly interested in research offering insights into the social attributes of dominant economic elites and their interdependencies with the political sphere through think tanks, clubs and informal groups. We also welcome papers that offer new empirical perspectives or analytical tools to understand how corporate networks are embedded into non-corporate forms of sociability, thus facilitating the connection of the economic realm with other social spheres. Papers may also explore how interlocking directorates help understand the transformation of business elites, especially when they are confronted with socio-political or financial crises. Finally, the session welcomes innovative approaches that combine social network analysis with qualitative or other quantitative methods (multiple correspondence analysis, sequence analysis, etc.).

 

Tomáš Diviák, Peter Carrington, Paolo Campana
 
The importance of social networks for analyzing and explaining criminal behavior has been widely recognized. A wide range of illegal activities, such as drug trafficking, human smuggling, or terrorism requires coordination among offenders to be successfully performed. It is not surprising, therefore, that the network perspective on crime has recently gained popularity, both among academics and law enforcement practitioners, as it captures the essence of such activities.
 
However, the study of criminal networks is challenging. Data collection is difficult in situations where subjects themselves aim not to be detected. Gathering first-hand evidence on such phenomena is therefore extremely difficult, and in some cases dangerous. Scholars have thus relied on police data, such as arrests, or investigative evidence, such as electronic surveillance or phone records, to build an empirical base for their analysis. A second challenge is methodological, i.e. matching/developing the right statistical models based on the specificities of criminal networks to adequately test criminological theories, allowing to move beyond descriptive network measures.
 
This session is dedicated to innovative research at the intersection of network analysis and criminology. We welcome a wide range of submissions focused on criminal networks, including methodological, theoretical, and empirical studies. Topics may include: collection of criminal network data, testing theories of co-offending, victimizations and violence using network data, case studies of specific criminal groups, and statistical modelling tailored to the complexities of criminal network data.
 
Keywords: covert networks, criminology, methodological innovation, co-offending, violence, organised crime, illegal markets.
 
Target group: both applied and methodological researchers interested in criminal network analysis, and law enforcement professionals. This session aims to bridge disciplines, to inspire discussion and collaboration.
 

Lindsay Young

 

Social networks and the methods used to analyze them have captured considerable interest among clinical, epidemiological, and behavioral health researchers. Now, widespread use of digital technologies, for example online social networking sites (e.g., Twitter, Instagram, Facebook, Reddit, Dating Apps), mobile phones, and other wearable devices, has created new sources of digitally archived, near real-time network data with immense potential for providing insights about a wide range of health-related outcomes and processes (e.g., infectious disease surveillance and transmission, health information- and care-seeking, norm formation, social support, and other peer influence processes), while also providing new opportunities for health care engagement and intervention. In this session, we seek papers that explore the relationship between digital social and communication networks and health-related outcomes, behaviors, and processes. We welcome studies that feature a wide range of network analytic techniques including egocentric network analysis, stochastic network models, semantic/text network characterization, and other computational approaches for both cross-sectional and longitudinal network data.

 

Omar Lizardo, Alessandro Lomi

 

Marking fifty years since its publication, Ron Breiger’s 1974 paper on “The Duality of Persons and Groups” is central to a lively research agenda anchored in analyzing two-mode (affiliation) networks. At the same time, the idea of duality, pointing to the co-constitution or co-structuring of entities across different levels of social organization, has become one of the core concepts in the field. Accordingly, during the past five decades, network scholars have exploited and generalized Breiger’s duality idea “beyond persons and groups” to apply to all settings featuring such dual patterns of cross-level coupling. This session seeks to feature papers pushing Breiger’s duality idea forward both in terms of formal methodological innovation and substantive application to core issues in social network analysis and modeling. These may include (among others) advances in dual projection approaches, dual community detection, positional analysis, algebraic representation, dynamic and multilevel modeling of two-mode networks. Papers seeking to move “beyond duality” methodologically and substantively will also be given strong consideration.
 

Marco Pelliccia

 

The aim of this session is to discuss social and economic phenomena by using tools from both Network Science and Economics. Conditional on the number of submissions, we could divide this session into two, where one would focus on network formation models while the other on strategic interactions on given networks.

 

Marina Hennig

Family is a community with strong ties, in which several generations care for and take responsibility for each other. It is a private social network of a special kind, which is established again and again by the family members. Thus, this concept of family deliberately distances from the idea of living and working together with unmarried children and emphasizes social relationships, especially mutual help, and empathy, with a wide circle of related and in-lawed persons.
 
Family scientists illuminate the multifaceted network “family” from different perspectives. A broad area of social science research examines social networks and analyzes the family as an informal social network. The focus here is on the question of the importance that the family network has, for which areas of life it is effective and in which way, how it is grounded, and how it changes over the life course.
 
In this context, research papers using both quantitative and qualitative or mixed methods are welcome. In addition to empirical contributions, methodological and/or theoretical contributions from different fields are also welcome (e. g. family networks in transition – network individualization, family networks in different cultures, family relationships over the life course, family networks and care or family time, connectivity, and social media)
 

Vera de Bel, Marlène Sapin, Julia Sauter, Eric D. Widmer

 

Life-course trajectories and transitions are intertwined within the complex web of family and personal relationships. These networks may provide individual network members with resources, supporting them through life-course events and transitions. However, these networks, depending on their composition or the pattern of interactions, may not only have a positive influence on the individual members of the network. Family and personal networks may also cause stress or strain at both the individual and network levels. Additionally, family and personal networks change over time, which may have consequences for access to resources, affecting individual network members’ well-being, behaviors, and life chances. This session invites papers on personal and family networks during different stages of the life course. We encourage submissions that focus on the transition into adulthood, family formation, union dissolution, transition to retirement, and aging. However, we also welcome studies on other life-course changes. Both quantitative and qualitative studies on specific normative or non-normative life events are of interest to this session.

 

Katja Mayer, Zachary Neal, Juergen Pfeffer

 

This session delves into the complexities of gaining and giving access to network data, presenting numerous challenges for researchers. Especially within the realm of social media, recent years have witnessed shifts in data access methods, such as APIs, data visits, and scraping data from platforms. However, some access methods often conflict with the licensing or usage terms. Furthermore, access to data from organisational, financial, biological, or health networks grapples with user privacy, ethical issues, and evolving regulations.
 
With the increasing attention to open science, researchers encounter pressures from funders, journals, and their academic peers to open and share their data. This movement, championing transparency and reproducibility, introduces its own challenges. Balancing data acquisition hurdles with sharing requirements adds layers of complexity to the research process. Merely visiting data—especially remotely—without understanding its completeness, sampling methods, etc., poses challenges. Archival data might lack context or harbour unseen biases, complicating its secondary use. In contrast, field-gathered data often have issues with consent, representation, and timeliness, which make them challenging not only to access but also to share. Beyond academia, these challenges have wider implications. Professionals in journalism, public policy, and more face comparable hurdles in their pursuit of network data-driven insights.
 
This session seeks presentations that are reflecting on personal experiences with access strategies, emphasising the interplay between data access and quality. How do researchers today access elusive network data unprepared for scientific use? What data, meta-data, or descriptions are essential for secondary data usage to ensure both integrity and ethical considerations? How have researchers successfully shared their data, information, and methodologies? In this session, we aim to dissect these challenges but also the emerging innovations in network data access. We welcome presentations that share personal experiences with intricate data access and quality, illuminating the broader consequences of these changes, and collaboratively exploring avenues for rigorous, ethical, and impactful research. Based on the presentations and insights from this session, a special issue is planned to further disseminate and explore these topics.
 

Elisa Bellotti

 

Social network research studies the mechanisms that drive formations of network structures as well as the outcomes of such structures on social behaviour. A well investigated area of research focuses on gender differences in network formations and outcomes in personal and professional networks. Researchers have looked, for example, at the different styles of socializations of boys and girls in early age, varieties of gendered network structures in different cultures, gender differences in peer networks and educational outcomes, gendered structural and cultural constrains of network strategies in organizational studies, different network positions and relational strategies between men and women at work, gender unbalance in academic networks and interlocking directorates.
 
This session wants to bring together interdisciplinary perspectives on gender similarities and differences in social networks which might be investigated with a variety of methods and modelling techniques. We welcome both highly quantitative modelling studies as well as qualitative research that looks at how discourses and narratives may impact the relational strategies embedded in network structures. We also welcome research that expand the very definition of gender to investigate peculiarities and differences of LGBT social networks.
 
Topics of the session might include, but are not limited to:
 
• Gender differences in structure and composition of personal networks
 
• Gender differences in tie formation in early life
 
• Gender dynamics in educational settings
 
• Gender and social support over the lifetime
 
• Gender, social capital and brokerage
 
• Gender differences in interlocking directorates, academic networks and organizational studies
 
• Gendered narratives in relational strategies
 
• Gendered perceptions of SNA
 

Paul Expert, Paola Zappa

 

Healthcare has undergone a profound transformation over the past few years, further accelerated by the aftermath of the COVID-19 pandemic. This shift has unveiled both opportunities for global collaborations on complex processes and projects, and local shortages and shortcomings. Concurrently, the digitalization of healthcare has witnessed unprecedented growth, thus offering new promise to address some of the most pressing issues by improving the access to patient data, empowering patients and multiplying the communication channels between healthcare workers.
 
For instance, the emergence of informal communication means, e.g. apps and virtual platforms, has changed the way healthcare workers communicate and how patients can interact with the healthcare system. These innovations have thus improved information sharing between healthcare workers, enhanced feedback and monitoring processes, streamlined training programs and fostered new ways of collaborating in clinical and research endeavors.
 
This transformation can be felt and put to use at different levels, from local specialist clinical teams to information handover between shifts, within hospital multi-specialist teams, inter-hospital patient transfers, and telemedicine platforms connecting healthcare professionals across continents, such as virtual robotic surgery teams. Despite the rapid proliferation of these technologies, tools and practices, their functional aspects and implications on patient outcomes and healthcare systems in general remain elusive. Areas which require further investigation include, but are not limited to:
 
• Ethical issues arising from the digitalization of information sharing
 
• Structure of information exchange (medium, timing)
 
• Direct versus indirect information sharing: information sharing among individuals or interactions between individuals and apps/platforms
 
• Patient transfer within and across hospitals
 
• Efficacy of communication between specialist teams during the COVID pandemic, e.g. ICU
 
• Telemedicine and spatially distributed care teams
 
• Effect of new communication means on patient outcomes, collaboration patterns, research outcomes and innovation.
 
• Formal (EHR) versus informal (apps, in person interactions) communication patterns and effect on patient outcomes
 
• Patients interaction with healthcare systems and healthcare workers
 
We welcome theoretical and empirical papers that contribute to the debate on these and related areas, as well as methodological papers offering insights on the treatment of digital healthcare data.
 

Tobias H. Stark, Lars Leszczensky

 

More and more researchers use social network analysis to better understand intergroup relations. Studies using cross-sectional (e.g., ERGM, ego-centric analysis) and longitudinal (e.g., SAOM) network analyses have established that social networks are segregated along ethnic, cultural, and religious lines.
 
However, research has only begun to exploit the potential of social network analysis for understanding the processes behind the emergence of intra- and intergroup relations and the causes and consequences of such relationships, such as intergroup attitudes, group identities, and group-related norms and behavior.
 
This session invites theoretical, methodological, and empirical contributions that aim to deepen our understanding of the emergence and consequences of intergroup relations in social networks.
 

Robert W. Krause, Per E.R. Block, Nynke M.D. Niezink, Christian E.G. Steglich

 

While some networks are static, many social relations change over time. Important insights into social networks can be obtained with the help of longitudinal observation designs. Such designs can be of a varied nature. Panel data is the structure used traditionally for self-reported networks; regular time series and time-stamped data can be obtained from official or automatic records; but this does not exhaust the types of longitudinal network designs. Corresponding to these differences in data collection, a variety of longitudinal methods of analysis have been developed, such as continuous-time actor-oriented and tie-oriented models for panel and time series data, network autoregressive models for time series at regular intervals, and network event models for data with a fine-grained time resolution. Some of these methods are based on actor-oriented models, others on tie-oriented models.
 
This session will be open to methodological as well as applied presentations about models for network dynamics. Presentations can have a mathematical, statistical, theoretical, or empirical subject-matter focus, as long as they are relevant for empirical social science. We welcome applied work bringing new insights into our understanding of how networks change, theoretical contributions on how networks evolve, advances in data collection for longitudinal data, and new methodology for studying network dynamics.
 
Keywords: network dynamics, longitudinal networks, actor-oriented models, relational event models, DyNAM, LERGM, TERGM, Siena, relevent, goldfish.
 

Filip Agneessens, Samin Aref, Nicholas Harrigan, Eva Jaspers, Giuseppe Labianca, Zachary Neal

 

This organized session focuses on the co-existence of positive and negative ties in networks across different domains and the need to study positive and negative ties together in order to better understand network dynamics, as well as processes and outcomes within these networks. We encourage a wide range of submissions. Example works include (but are not limited to): Methods and measures pertaining to signed networks (in social, economic, political, biological, financial, informational, or physical contexts); modeling and analysis of negative ties; understanding how structural balance affects volatility in financial markets; explaining the inner workings of political and legal bodies such as legislatures or courts; understanding how threats within a network create needs for allies, particularly in international relations; examining where bullying emerges in schools or organizations; exploring how positive and negative emotion are structured within our cognitive semantic networks; how perceptions of negative ties poses unique challenges in organizational research; examining how relational ambivalence affects relational trajectories; and how subgroup fault lines affect intra- and inter-group conflict.

 

Giuseppe Giordano, Giancarlo Ragozini, Maria Prosperina VItale

 

The large amount of textual data available in digital space represents a new challenge for data analysts in search of new statistical methods, scalable algorithms, and enhanced visualization tools to face the intrinsic complexity of such kinds of data.
 
The different steps of any network textual data analysis imply a sequence of demanding tasks, starting from data collection and preparation; defining complex network data structures; implementing algorithms and techniques to deal with different levels of data complexity; and analyzing and visually representing network data.
 
Scientific debate offers many solutions under the framework of Text Mining, Deep Learning, Network Science, etc. We may find pure algorithms, statistical methods, and machine learning techniques based on the specific scientific field. Some methods are general purposes; others deal with definite applied problems.
 
This session aims to collect contributions focused on theoretical, methodological, and empirical aspects related to textual network analysis, visualization, and graph embedding.

 

Maria Prosperina Vitale, Giuseppe Giordano, Giancarlo Ragozini, Isabella Sulis

 
The quality of an educational institution is strictly related to its capability to enhance students’ performances and to reduce the inequalities related to their initial conditions. Many researchers report the persistence of differences in key educational performance indicators across institutions and geographical areas. The family and the school environment as well as the peers have an important influence on educational choices and learning outcomes.
 
This session is addressed to researchers who analyze how educational inequalities and their mechanisms of reproduction are affected by social contexts and relations. Specific attention will be devoted to the role played by high schools and universities in shaping interactions among peers and how these relations affect educational choices.
 
Methodological developments on the use of hierarchical and network models for analyzing social influence mechanisms and peers’ effect as well as empirical applications on complete and ego-centered network data in education are strongly encouraged.
 
Keywords
– Peer effect
– Education inequalities
– Social influence
– Statistical models
– Student performance
 

Roberto Rondinelli, Lucio Palazzo, Riccardo Ievoli, Gordana Marmulla, Filipe Manuel Clemente, Kristijan Breznik

 

Social network analysis is an emerging paradigm within sports research used to study athletes’ and team performances, dynamics within a team, playing patterns of games, or competitiveness of sports leagues, among others (Wäsche et al., 2017). Sports is a domain suitable for network research that considers the interdependency not just between actors (e.g., teammates) but also between actors and collectives (e.g., the players and the teams to which they belong). This area of research strongly supports the application of the network perspective in sports (e.g., by considering the individual as part of a team that behaves collectively or, more generally, the individual and/or the team as part of a sport-related social environment). Moreover, the increasing availability of data has given rise to sports analytics tools and the transfer of methodologies from other fields (particularly from network analysis) into a broad range of sports that allowed to address relevant research questions. For example, recognizing the strengths and weaknesses of individual players within a team can help to make better decisions and shape the strategy in such a way that greater success is achieved in terms of sporting results, economic aspects, and player satisfaction.
 
The proposed session focuses on contributions and original applications regarding network analysis in sports. Potential topics may address, for example, unveiling the key elements regarding tactics and strategies in sports (interaction networks), analyzing the relative performance of athletes or teams (competition networks), or investigating the role of trading and exchanges (affiliation and inter-organizational networks) or friendship among team members (intra-organizational networks) on sports results. The session aims to bring together experts from different fields, such as computer science and social scientists, to contribute to sports science, which are all interested in applying and expanding these topics from the network perspective. In this session, we welcome empirical and new methodological contributions exploiting the role of network analysis from popular to less-known sports, including (but not limited to):
 
(1) Local network structures
 
(2) Temporal networks
 
(3) Network indicators and sport outcomes
 
(4) Signed networks
 
(5) Multimodal networks
 
(6) Multilayer networks
 
While we enthusiastically welcome network-related studies, we also encourage research that involves multi-area analysis. This may include approaches like integrating team performance analysis using networks with additional analytical techniques or combining data from other sources, such as physical and physiological performance metrics. The same principle can be applied to various other contexts.
 

Claudia Zucca, Mario Diani, John McLevey, Lorien Jasny

 

The study of how different beliefs are related to one another has a long history, dating back to Philip Converse’s comparison of the beliefs held by the public and elite on international relations. The ‘relational culture’ perspective argues that understanding the relationships between attitudes, beliefs, and values is crucial to understanding society as a whole, as they provide meaning and order. By treating these relationships as a network structure, researchers can explore new questions and theories regarding cultural formation and change within the social networks of society. This approach is used across a variety of disciplines, including anthropology, political science, psychology, and sociology, and employs classic comparative methods such as directed acyclic graphs and Bayesian Belief Networks, as well as complex systems methodologies such as causal loop diagrams, semantic networks, and system mapping. However, this work is often isolated within individual disciplines and uses different terminology to describe similar approaches.
 
This organized session invites innovative papers that examine networks of connections between beliefs using a variety of methodological approaches and from a broad range of disciplines. Specifically, we are interested in papers that focus on networks where beliefs, ideas, or concepts form the nodes of the network. Both methodologically focused works and novel substantive applications will be considered as long as they explicitly focus on the relationships between beliefs. This organized session aims to bring together the various approaches to understanding belief, such as mental models, fuzzy cognitive maps, cognitive-affective mapping, and belief networks, by highlighting their shared reliance on a network to represent data.
 

Valeria Policastro, Annamaria Carissimo, Luisa Cutillo, Francesco Santelli, Davide Vega

 

The session will cover different types of methodologies and applications for network clustering and validation. These will address important and challenging problems in network analysis that come across in different application fields, especially in social science.
 
The state of the art of clustering validation in networks relies on different approaches, such as analysing the network structure using information theory-based methods, comparing partitions detected by different community detection algorithms or analysing the network robustness to perturbation.
 
Different types of community detection methods have been developed over the years, with more or less broader applicability, and yet the reliability and the meaningfulness of the results are still an open challenge.
 
The session is open to contributions dealing with cutting-edge quantitative and qualitative methodologies focusing on complex networks such as attributed, weighted, directed and multilayer networks. These topics are particularly demanding and of significant interest within the research community. Moreover, also interesting, and innovative applications in the field of network clustering and validation are welcome.
 
Despite the growing interest in this field, clustering and validating networks is still an ongoing issue. The aim of this session is to investigate the most recent contributions of methods and applications on this topic.
 
Keywords: validation, clustering, community detection, weighted, attributed, directed, multilayer
 

Angela G. Spencer

 

Implementation science is a growing field, dedicated to speeding up the adoption of evidence-based health interventions or practices (EBPs) in health systems, organizations, and communities. Social network analysis can be used to plan implementation activities, identify change agents and key stakeholders, and measure adoption or diffusion of knowledge and practices. Presentations that link implementation science theories or frameworks with study designs are encouraged.
 
Topics may include:
– Use of network methods within Implementation Science frameworks
– Network influences on EBP adoption
– Diffusion of EBPs within networks
– Network characteristics of program recipients
– Changes in networks resulting from EBP implementation activities
 

Scott Duxbury, Ben Rosche

 

An extensive literature in network analysis examines structural characteristics of networks, such as network cohesion, network centralization, network clustering, and network composition (Moody and White 2003; Krackhardt 1993; DiMaggio and Garip 2012). Researchers are increasingly interested in analyzing the determinants of such structural characteristics. These questions relate to a large research program in the social sciences studying how micro-level network selection decisions shape macro-level network outcomes (Coleman 1990; Granovetter 1973; Hedstrom and Bearman 2011; Gërxhani, De Graaf, and Raub 2022). Recent methodological advances in statistical and simulation approaches for evaluating micro-macro linkages in social networks have contributed to a burgeoning literature on the micro-level determinants of specific structural network characteristics (An, Beauville, and Rosche 2022; Robins, Pattison, and Woolcock 2005; Snijders and Steglich 2015; Duxbury 2023a; Duxbury 2023b). In this session, we invite papers that apply and develop methodological tools for micro-macro network analysis. We specifically are interested in papers that seek to explain specific network structural characteristics (e.g., clustering, segregation, cohesion) as a function of micro-level selection processes. Empirical, theoretical, and methodological papers are welcome.

 

Christian Stegbauer, Iris Clemens

 

Culture should play a more important role in network research. This is because both social forms and meanings are important for the formation of networks. Networks and cultures are tightly interwoven with each other. It can be shown also empirically, how cultures are connected with structures of relationships in networks. Networks gets constructed and reconstructed through cultures, and vice versa. As meaning let relations emerge, and stabilise or prevent them, culture structures social relations in various ways. This leads to differentiations between cultures and networks: e.g. different cultures make certain relations more or less likely.
 
In certain structures, an established culture is conveyed and further developed. Culture in this context refers primarily to everyday life: practices, understanding of symbols, conventions, what people consider as correct, what they like or do not like. How people behave can also be described as (part of) culture. This means that when we analyze social structures in networks, they are always linked to cultural content. The perspective of culture leads to deeper insights to network analysis because reasons for the formation and maintenance of networks become visible. Therefore, the inclusion of culture is an important aspect in network research.
 
For our session, we invite all network research who consider culture in their analyses in one way or another. We are interested in conceptual contributions to the relationship between culture and networks, as well as in empirical and other analyses of networks that focus on culture.
 

David Zbíral, Cindarella Petz

 

A growing number of studies in historical and archaeological research have trailblazed relational approaches to the human past, and helped us to adapt network science methodologies to the specificities of humanities data. As graphs have become an established tool of modelling data on the past within the Digital Humanities, a growing reflection of the use of technologies and algorithms has been accompanied by theoretical consideration of their critical application. Moreover, it is becoming clear that archaeological and historical data sources and research topics pose intriguing challenges and opportunities to social (historical) network analysis and network science in general.
 
This session aims at empirical, methodological, and theoretical presentations concerning any historical period and any geographic area, which use formal methods and/or build upon the theoretical foundations of network analysis to shed light on the human past.
 
Possible topics might include:
 
analysis of past networks (social, infrastructural, semantic, etc.);
 
change of historical networks over time (longitudinal, temporal, …);
 
collection, retrieval and modelling of network data from historical sources (textual sources, artefacts, …);
 
peculiarities of incomplete, missing, uncertain and fuzzy data for historical and archeological research;
 
network extraction from historical texts;
 
semantic network analysis of historical texts;
 
material sources as proxy evidence for social phenomena;
 
transportation, migration, and diffusion;
 
economy from a network perspective.

 

Victor Leo Rosenberg

 

The Networks and Venture Capital session offers a forum for researchers to explore the intricate connections between social networks and the world of venture capital. In this session, we welcome presentations that delve into the multifaceted nature of networks within the realm of venture capital. These networks can encompass connections between investors, entrepreneurs, startup teams, and the broader innovation ecosystem. We encourage contributions that examine the dynamics of information flow, resource sharing, and collaboration within these networks.
 
Substantive areas of research within this session may encompass topics such as the formation and evolution of investment syndicates, the role of innovativeness in deal-making, the influence of geographic proximity on investment networks, and the effects of macroeconomic changes on venture capital networks.
 
We invite innovative approaches that combine social network analysis with other methods to provide a holistic understanding of the intricate relationships between stakeholders. This session aims to foster a multidisciplinary space where scholars can share insights, methodologies, and empirical findings to advance our understanding of how social networks shape the venture capital landscape and, in turn, impact innovation and economic development.
 

James A. Coutinho

 

Effectiveness of a whole network can be defined as the attainment of positive network-level outcomes that could not normally be achieved by individual participants acting independently (Provan & Kenis, 2008: 230). Few scholars have attended to how organizational networks as a whole, consisting of numerous interdependent agents within the bounds of an organization, can be actively managed to reach individual and collective goals. Thus we lack a thorough understanding of how organizations can purposefully create network structures to achieve desired outcomes. Outcomes of interest at the whole-network level are various, including (but not limited to) resilience (e.g. the network is not easily disrupted or can adapt to rapid change and external shocks); performance; efficiency; and the satisfaction of organization members’ needs. Advancing research on organizational network effectiveness at the whole-network level is of value to scholars and practitioners concerned with understanding and managing complex modern organizations. This session will bring together research papers that contribute to our understanding of how organizations can form effective networks to achieve collective goals and promote collective outcomes.

Spyros Angelopoulos, Emmanuel Lazega, Francesca Pallotti, Paola Zappa
 
The networked nature of organizations creates a complex ecosystem where individuals, groups, units, and other organizations are entangled. Such an entanglement shapes organizations in a dynamic way and affects their outcomes at multiple levels. This session aims to bring together studies on organizational networks addressing antecedents, dynamics, cross-level processes, and outcomes.
 
Submissions can refer, but are not limited, to the following areas of research:
– Micro-foundations of organizational networks: How individual characteristics and cognitions affect the emergence of network structures and how these network structures affect individuals.
– Dynamics of organizational networks: How network structures at various levels co-evolve and affect one another, as well as organizational processes and outcomes.
– Time-dependence in organizational networks: How organizational networks at various levels change at different paces over time.
– Overlap and interplay between social and other kinds of networks within and across organizational settings: How organizational networks are affected by the affiliation of individuals, or organizations to events or contexts.
– Organizational networks and the future of work: How new technologies (e.g., digital platforms, Artificial Intelligence, Virtual Reality) and new forms of organizing (e.g., distributed, boundaryless, and hybrid organizations) shape, support or hinder organizational networks.
 
We welcome both theoretical and empirical contributions addressing various aspects and implications of organizational networks research.
 

Dimitris Christopoulos, Christina Prell, James Hollway, Manuel Fischer, Petr Ocelik

 

We propose an Organized Session on Political Networks. The Session should provide a multidisciplinary space of convergence for scholars that, while holding diverse research interests in the study of politics, policy-making and political behavior, share an analytic approach to network processes in political life, coupled with strong attention to the integration of theory and empirical data. Political networks are conceived of in a broad sense – as defined around political actors, events that are relevant to the political biographies of individuals as well as around the use of digital communication technologies within political dynamics, among others. Thus, ties can consist of exchanges of resources, information, and symbols, as well as of collaborations and communications that may occur both on- and offline. Substantive issues that researchers in political networks have been dealing with are policy networks around climate change on the local, national and international levels, networks of social movement organizations, comparisons of networks across different institutional contexts, or political interactions within new social media, among others. Organized Sessions on Political Networks have been well-frequented at past Sunbelt / EUSN conferences; the session is endorsed by the Standing Group on Political Networks of ECPR (European Consortium on Political Research).
 

Andreas Herz

 

Qualitative approaches in Social Network Analysis (SNA) study relational structures by means of qualitative methodology. A variety of methodological traditions and theories inspire this research, including conversation analysis, ethnography, small story research, field theory, social world theory and interactionism. In empirical studies diverse qualitative methods are applied and different kinds of data are taken as qualitative data material including interviews, observations and visualizations. Fundamental to the qualitative approaches is a close entanglement of theory and method in the sense of a methodical holism.
 
In this session we want to engage in a discussion on how different traditions and schools of thought orient qualitative research on social networks. We invite participants to present their empirical approaches, to discuss how they integrate theory, methodology and method in their network research and how they understand relationships and relational structures in their qualitative research approaches.
 
Contributions may tackle questions such as the following:
 
How do qualitative methodical procedures relate to methodological and theoretical positions and how can they be integrated to analyze social networks?
 
What do the various strands of qualitative research offer for the analysis of social networks?
 
What are the comparative (dis-)advantages of different qualitative perspectives (such as narrative inquiry or ethnography) for the analysis of / when analyzing social networks?
 
How do we integrate qualitative research strategies with perspectives taken from (quantitative) structural analysis and how can this be done in a theoretically and methodologically consistent manner?
 

Zachary Neal

 

R has become a dominant platform for network analysis. Packages such as igraph (for general analysis), statnet (for ERGM), and RSiena (for actor oriented stochastic models) are already well-known and widely-used. However, many other R packages exist that perform more specialized network analyses. These packages can simplify analysis, or open up new analytic possibilities, but are sometimes difficult to find. This session invites papers that introduce and demonstrate new or updated R packages for network analysis.

 

Frederick Kin Hing Phoa

 

In the current big-data regime, a large-scale social network, despite its sheer size and complexity, has received much attention from researchers of many different fields, including social sciences, network sciences, economists and statisticians. The grand aggregation of knowledge contributions from these fields generates many inspiring outcomes for this interdisciplinary research area. This organized session aims at introducing recent advances in the statistical analysis and mathematical modeling in large-scale network data, and their applications in social networks. It is expected to gather experts to discuss recent advances in sociology, information science and statistics, and to analyze the networks from different point of view. The topics include, but not limited to, network structure characterization, network data analysis, network dynamics, network modelling, network data visualization, real-life applications and so on.

 

Francisca Ortiz Ruiz, José Luis Molina, Isidro Maya Jariego
 
Social network analysts’ community, working in Latin America, Spain, Portugal, and other countries, is vibrant, diverse, growing, and dedicated to research and the applications of SNA to critical social problems. Since the XXI Sunbelt (Budapest, 2001) the workshop “Mesa Hispana” has gathered researchers interested in SNA from the Latin American world aimed to develop this community within the INSNA framework (Maya Jariego & Molina, 2004), helping to initiate and maintain links amongst this transnational community of researchers. Sunbelt 2024 is an auspicious occasion to bring together community representatives, start new collaborative projects, have close theoretical and practical discussions, and review recent developments across disciplines.
 
In this panel, the objective is to have a space for discussion about the latest advances made in social network research. This panel aims to promote collaboration among people who publish research in Spanish or Portuguese, apart from English. This panel has historically been a bridge between Spain, Portugal, and Latin American countries and the international communities of social network analysis, a vision we would like to keep. This panel gives the space to bring together ideas and planning initiatives for the following years.
 
Presentations can be in English or Spanish; as speakers prefer. We specially encourage to apply people in different stages of their careers, that do not feel comfortable presenting in English, or for those who this is the first time presenting in the network’s community.
 

Michel Grossetti, Quentin Chapus

 

In social network analysis handbooks, it is customary to distinguish between personal network approaches and complete network approaches. Both approaches have their advantages and limitations, but what they have in common is that they produce static representations of networks. There are other approaches, one of which can be called the relational chain method. Famous examples include Milgram’s investigation of “small worlds”, Howell Lee’s study of women seeking abortion doctors, and Granovetter’s study of access to employment. In this method, the aim is not to analyze static structures, but rather to identify the activation of interpersonal relationships in processes of access to resources. The aim of this session is to present work using this approach, and to discuss the common points according to the social situations concerned: length of chains; types of links; multiple chains; conditions for activating links; etc.
 
References
 
Michel Grossetti, Jean-François Barthe, Nathalie Chauvac, 2011, « Studying relational chains from narrative material », Bulletin of Sociological Methodology, n°110, pp. 11-25.
 
Zachary P. Neal, Jennifer Watling Neal, “That’ll move the chains: Collecting network chain data”, Social Networks, Volume 69, 2022, Pages 35-44.
 
 

Domenico De Stefano, Viviana Amati, Marjan Cugmas, Dominika Czerniawska, Alejandro Espinosa-Rada, Luka Kronegger, Susanna Zaccarin

 

Scientific collaboration networks have been a main area of interest to social network researchers for the study of socio-cognitive ties by investigating scientific inequalities, the formation of different morphological network structures (such as paradigmatic groups, specialties, or invisible colleges), knowledge production, their interrelation and impact on public policies, among others. While most of the research often uses the formal channels of communication of science as a proxy of social ties (e.g., through the usage of co-authorship, citations, or thesis supervision), there is an increased interest in gathering more data by considering the informal channels of communication in science through classical research methods from the social science (e.g., surveys, interviews, ethnographies, secondary documents) or the expansion of established or new and more sophisticated large-scale data to understand the inner workings of science and knowledge (e.g., Web of Science, Scopus, Dimensions, SciSciNet) and their intertwines in the contemporary society. In this session, we are interested in expanding and moving beyond bibliometrics towards a more comprehensive social network approach for the study of scientific networks to discuss data quality and data collection, new methods, and models for the study of the structure of scientific collaboration networks as well as their evolution over time. We also welcome empirical applications in the field, including but not limited to: local and global scientific networks, policy-driven change in scientific collaboration, politically driven shift in science and knowledge production, addressing global challenges through scientific collaborations and consortia.

 

Professor Dame Heather McGregor

 

There will be a half-day Social Capital themed series of sessions presented in collaboration with the International Social Capital Association. This will start with an in-person panel session entitled ‘The Role of Social Capital in addressing Disadvantage’ with invited speakers, chaired by Professor Dame Heather McGregor.

 

This will be followed by a number of in-person paper sessions. All sessions will take place during a single afternoon during the conference (exact day to be confirmed when final schedule announced, will be one of 26/27/28/29 June). Submission guidelines are as per the main conference website.

 

All social capital-themed papers are welcome and successful submissions will be grouped appropriately. At least one person must be in attendance to present in person. A separate online session may also be arranged depending on demand.

 

Zsofia Boda, Robert Krause, Isabel Raabe, Andras Voros

 

The empirical study of social influence processes has become an increasingly popular topic in social network research in the past years. Advances in data collection and statistical modelling have made it possible to explore and distinguish various influence processes in longitudinal data on networks and individual behaviour. For instance, it is now possible to study which actors are likely to influence which other actors in a network. Further, we may also compare the influence from specific actors and from being in a certain network position, such as influence from and on popular individuals. Social influence is conceptually not even limited to network-and-behaviour studies. We can also investigate mechanisms of network-network influence, where one (one-mode) network defines what the reference group of social actors is that exerts influence, while another (one- or two-mode) network indicates what is being influenced. In this session, we welcome methodological, theoretical, and applied contributions to the study of social influence in networks, as long as they are relevant for empirical research.

 

David Tindall, Mario Diani

 

Policy networks consist of organizational actors interacting with each other in a variety of ways to support, oppose, implement, other otherwise shape policy options. Depending on the substantive policy domain, different types of actors that are typically involved in policy networks include governments, think tanks, business organizations, scientific organizations, and social movement and other civil society organizations. This session welcomes proposals that analyze various aspects of social movement organizations and/or civil society organizations in the context of policy networks, and the policy process.

 

Ana Lucia Rodriguez De La Rosa, Ana María Jaramillo Mejía

 

Individuals living in Low and Middle-Income Countries (LMICs) represent the global majority of the world, while remaining an understudied setting in network science research. In the context of non-WEIRD (Western, Educated, Industrialized, Rich, and Democratic) societies, well-being, and health challenges meet unique environmental and cultural landscapes, such as limited resources, extreme poverty, government absenteeism, community violence, inequality, and pronounced gender disparities.
 
Real-world social networks in LMIC communities can become instrumental and vital sources of welfare, knowledge, and support, in ways that may differ from more urbanized, wealthy, or democratic settings. Often becoming the sole source of support (especially en rural settings) relationships in the global south can become more sustained in time, harder to define (negative and positive effects simultaneously), and accumulate more power and information, if compared to contexts in which other sources of welfare are more readily available.
 
Empirical Social Network research in the LMIC context faces additional challenges, ranging from the logistical and security conditions for data collection, to the deep community partnerships and involvement to successfully design ethical, reliable, and culturally sensitive tools and methodologies. This session will highlight the results of observational, interventional, or reflective research papers that center on the role of social networks in LMIC societies.
 
The session will be devoted to the role of social networks as mechanisms for enhancing welfare; the commonalities or unique findings in the global south; interventions based in social network traits or algorithms; mixed methods studies; contagion dynamics or cascade effects is socio-centric studies; the qualitative importance of diverse social ties; multi-layered or temporal networks; ego-centered research; or implementation work on successful research or dissemination strategies, including innovative methodologies, devoted to amplifying our knowledge on the role of social networks on LMIC settings. Review papers are also welcome.
 
This session will contribute to the global discussion of the role of social networks in welfare, and global development and health goals. Furthermore, we will highlight the approaches, research designs, and strategies that have been implemented to close the research disparity in representation of the global south; examining the unique challenges and possibilities of social analyses work in the context of LMIC.
 

Edda Rodriguez, Lacey Craker, Kyle J Self, Rebe Silvey, Ariana Johnson, Mariano Kanamori

 

Session theme: Addressing and mitigating health disparities and inequities requires methods to engage, model, and visualize the network of disproportionately impacted populations (i.e., sexual, gender, ethnic, and racial minorities). Social network approaches provide such flexibility, allowing researchers to design, implement, and analyze complex peer interactions that influence health outcomes. This session will highlight projects using innovative social network strategies to improve health outcomes across the health care continuum (e.g., prevention to treatment).

 

Michele Lee Barnes, Örjan Bodin

 

The planet is currently facing significant environmental problems – climate change alone is already affecting every region on Earth, and its impacts – including droughts, floods, and heatwaves – present a significant risk to human life and the ecosystems we depend on. These problems; ranging from resource depletion, to pollution, deforestation, and climate change threaten both social and ecological resilience; are in large part driven by human behaviour and people’s relationships with the environment. Moreover, whether environmental problems can be mitigated and managed to ensure long-term sustainability and resilience ultimately rests on whether and how people, organisations, and governments are able to come together to devise institutions, practices, and forms of governance that are effective and suitable for the tasks at hand. Recognising this, there has been growing and significant attention on the social dynamics associated with environmental problems, and how the entanglements of social and environmental dynamics condition resilience and the search for effective solutions. One critical insight that has emerged from this research agenda is that social (and ecological) networks are key. Just over 10 years ago, a foundational collection of work focused on social networks in the context of the environment was first published. This session will present a collection of chapters from a forthcoming book commissioned by the publisher Edgar Elgar that summarises the significant progress that has been made in this field since the publication of this foundational work just over a decade ago. Specifically, the session will demonstrate the utility of network approaches across a range of environmental issues at different scales (individual, community, regional, global). In doing so, it will highlight both conceptual and methodological advances that have contributed to our understanding of the critical role that social networks can play in driving environmental problems, and how they can potentially be leveraged to help solve environmental problems and contribute to a more sustainable and resilient future.

 

David Tindall, Mark Stoddart, Paul Wagner

 

This session will focus on networks and climate change, and will consider papers on theoretical, methodological, and substantive topics related to this theme, including organizational networks, virtual networks, discourse networks, and personal networks. Topics may include (but are not limited to) social movements, values and attitudes, community resilience, policy networks, climate change disinformation networks, political economic networks.

 

Christina Prell, Petr Ocelik, Martin Everett

 

Social network analysis cuts across many disciplines, and it is often combined with other approaches that adhere to a relational or connectivity set of assumptions. For example, in recent years, there has been much discussion on ‘what is social network analysis’, versus ‘what is network science’ and whether making such distinctions is even a useful or productive endeavor. In this session, we wish to showcase papers that combine (interdisciplinary) social network analysis with other connectivity-based approaches (qualitative or quantitative) with a focus on sustainability. We take a broad view of the term ‘sustainability’, and welcome papers that focus either on one or more Sustainable Development Goals (SDGs), as proposed by the United Nations (UN), or focus more generally on long-term perspectives concerning the well-being of future generations. Critical reflection on the mixing/combining of different connectivity/network approaches (or a comparison of their trade-offs) is also welcome.
 
Background: the inspiration behind this session comes from two sources. The first is a Marie Skłodowska-Curie Innovative Training Network (ITN) project, entitled i-CONN, which was funded by the European Commission, under their H2020 programme (https://iconn.network/). The Consortium consists of 10 Universities and three partner organizations across Europe, and brings together scientists from across a range of disciplines: Archeology, Astrophysics, Computer Science, Economics, Ecology, Geomorphology, Human Geography, Hydrology, Neuroscience, Policy & Political Science, Sociology, and Systems Biology. The goal of i-CONN has been to train a new cohort of researchers (15 funded PhD researchers in total) specialized in the developing field of Connectivity Science – a field that encompasses social network analysis, alongside other methodological approaches that aim to capture differing notions and aspects of connectivity.
 
The second inspiration comes from the recently established Rudolf Agricola School for Sustainable Development at the University of Groningen (https://www.rug.nl/rudolf-agricola-school/). This is a cross-faculty school that encourages and facilitates inter- and transdisciplinary collaborations on the topic of sustainability. Similar to i-CONN, this School hosts a number of scholars from network-related fields (e.g. social network analysis, network science, systems thinking, input-output analysis, etc.) who see a need for exploring the ways these “similar-yet-different’ methodological approaches compare and might be constructively brought together.
 

Paulina Erices Ocampo, Miranda Jessica Lubbers, Jimi Adams

 

While networks can provide opportunities to access beneficial resources, they can also constrain that access for some, generating inequalities in a variety of outcomes. Better connected people can access helpful information, enjoy stronger social support, reach better opportunities for social mobility, and even exhibit better health outcomes. In contrast, marginalized groups can have smaller social networks and experience reduced access to resources, information, and benefits. Identifying the mechanisms that foster access and mobilization of social capital—especially for immigrant populations—to overcome these disparities is central to understanding how well-being is attained and how inequities emerge.
 
In this session, researchers will present their work on social capital, social networks, and immigration. We invite topics unfolding benefits, liabilities, origins, outcomes, or mechanisms of social capital and how it is created and mobilized in social networks.
 

Ian McCulloh, Carolyn Parkinson, Matthew Lieberman

 

The SN2 is a dynamic forum for researchers, scientists, and practitioners to explore the profound intersection of social neuroscience and social network analysis. In an era of complex social dynamics and evolving technology, this conference aims to foster collaboration and the exchange of knowledge at the nexus of these two fields. We invite scholars from diverse disciplines to join us in an engaging dialogue and to present their latest research and insights.
 
Topics of Interest: Papers are invited on various aspects of social neuroscience and social network analysis, including but not limited to:
 
• Brain mechanisms underlying social behavior
 
• Neural correlates of social interactions
 
• Social networks in the digital age
 
• Neurobiology of information diffusion in networks
 
• Psychological and cognitive aspects of network formation
 
• Health and well-being implications of social connections
 
• Methodological advancements in social neuroscience and network analysis
 
• Ethical considerations in studying social neuroscience and social networks
 

Guy Harling, Dorottya Hoor

 

A key aspect of social networks as they relate to health is the support and advice that flows through the network. This support is connected to, but distinct from, network position/structure itself. We invite abstracts that consider any aspect of social support and health on networks, focusing on what flows through ties as causal mechanisms for network or health status change in individuals. This might include how health-related support is generated within networks, or how it is patterned across networks (e.g. by age, gender, social status). It might also include longitudinal analysis of how support or advice predicts health knowledge, behaviour or outcome, or how health predicts receipt of support.
 
In previous years, health topics have included substance use, sexual health, mental health and non-communicable health conditions – but other areas of research are welcome. While the sessions have primarily focused on quantitative analysis, qualitative and mixed-method approaches are welcome. We particularly welcome research from low- and middle-income settings.
 

Gil Viry, Marion Maisonobe

 

Social ties and social networks exist in and across geographical spaces. Network scholars have highlighted the critical role of social networks in spatial mobility of populations and the significant differences in the ways social groups develop their networks across space. Yet, the mainstream literature in SNA pays relatively little attention to spatial dimensions of social networks and remains largely disconnected from the vast body of research on spatial networks in geography and cognate fields, such as architecture, transport and urban studies. Important questions and approaches for analysing how network and spatial contexts intersect therefore need further development.
 
While space affects the formation, dynamics and effects of social networks, social actors shape space through their social connections and cultural processes. Analysing the intersection of network and spatial contexts yields conceptual and methodological opportunities and challenges.
 
In this session we are interested in:
– Theories, concepts and methods of analysing or visualising social networks in space
– Influence of space, place and spatial mobility on social network structures and dynamics
– Influence of social dynamics on networks of places, systems of cities, world systems
– Role of place and social actors’ experience of place in network formation through physical, cultural and geographical dimensions
– Spatial dimensions of personal networks over the life course or in different spatial settings (e.g. urban/ rural)
– Issues of power and social inequality related to the spatial dimensions of social networks
 
We welcome conceptual and methodological approaches from various research fields and disciplines using quantitative, qualitative or mixed methods.
 

Matthew Smith, Yasaman Sarabi, Riccardo De Vita, Guido Conaldi

 

Social Network Analysis (SNA) is being increasingly taught in various academic settings and contexts, either as a standalone subject or as a methodological tool within a specific discipline. There is often a focus on teaching various software packages as vehicles to introduce methodological concepts and tools. Whist teaching how to “practice” SNA is vital, there is also a need to balance this with understanding of relevant theories.
 
This event aims to provide a forum to the SNA community to exchange idea, best practices, and pedagogical reflections regarding teaching SNA, in particular how to balance theory and practice when introducing core SNA concepts.
 
We intend to have panel discussion of experts discussing the issues of teaching SNA, this will then be followed by presentation contributions.
 
We welcome submissions discussing any issue associated with the teaching of SNA, theory and practice, including but not limited to:
– Teaching network theory
– Teaching qualitative SNA
– Teaching quantitative SNA
– Teaching software for SNA
– Teaching SNA across different levels (undergraduate, postgraduate, postgraduate research and executive education)
– Opportunities, best practices, and challenges of teaching SNA
– Experiments and SNA
 
The contributions could be work in progress or completed studies. We welcome both theoretical and empirical studies, as well as those which are more focused on pedagogical reflections. Case studies, population-wide research, software illustrations are all welcome contributions. A variety of presentations styles are welcome, including interactive presentations.
 

Emily Cyr, Hilary Bergsieker

 

Although social network analysis gives us critical insights into complex interpersonal processes, these “objective” network measures do not always align with more “subjective” assessments of psychological states or beliefs. Recent work integrating psychological and social network approaches has revealed new insights into the sometimes paradoxical interplay between networks and individual experiences. For example, minority group members may report a subjective sense of social ostracization even when they receive an above-chance proportion of friendship nominations. Conversely, individuals who subjectively appraise themselves as having a high degree of social influence often overestimate their actual network centrality. This area of research — bridging classical network methodology with individual-level psychological measurement — points to a critical need for new cross-disciplinary work examining such discrepancies.
 
This session will centrally examine when and why inconsistencies may arise between so-called “objective” measures of network structure and more “subjective” assessments of individuals’ personal inner lives. We hope for a lively discussion on comparing the alignment between “objective” versus “subjective” measures and later network- or individual-level outcomes. We seek cross-disciplinary perspectives on links between collectively constructed social network measures and individually experienced subjective measures. We will leverage diverse theoretical lenses and methodologies to highlight topics such as (but not limited to):
– Why network indegree translates into felt inclusion for some social groups more than others
– Why self-assessed belonging might lead to an egocentric over-reporting of ties
– The relative explanatory power of “objective” network measures versus “subjective” psychological assessment (e.g., in predicting behaviour, workplace/academic outcomes)
Holly Baker
 

While we have interesting evidence from many different contexts that social networks are an important component of behavior and behavior change, the mechanisms of these dynamics are often missing from network research. In the meantime, public health researchers, international development agencies, and policy makers are increasingly focused on the role of social norms in behavior change, realizing that it is often ineffective to intervene on an individual without taking into account the social normative environment of that individual. Because of this many behavioral change interventions around the world are now being implemented with a social norms lens. Social norms, of course, do not exist in a vacuum, and social network analysis can be a powerful tool for understanding the social scaffolding on which norms are supported. This session will focus on the intersection of social norms and social network analysis. Submissions should consider social network factors in conjunction with social normative factors around a specific behavior or outcome. Submissions are welcome from any academic discipline.

Miranda Lubbers, Beate Völker, Michal Bojanowski

 

The Network Scale-Up Method (NSUM) was invented more than three decades ago to estimate the size of hard-to-count populations, based on aggregated relational data (ARD; questions of the type “How many people do you know who have trait x?”). Subsequently, it is employed in many cases for both estimating subpopulations of unknown size and for estimating network sizes by using populations of known sizes.
 
Since its invention, assumptions, methods and software tools have been improved and applied in many cases such as estimating risk for infections, number of victims of attacks, and mortality. More recently, the method has been used to estimate the size of the acquaintance network, i.e., the weaker ties of an individual, and the segregation across social cleavages.
 
This session will bring together papers that include NSUM for the analysis of network features both as explanandum, e.g. what are the conditions for variation in network sizes, and explanans, e.g., what are the individual and social consequences of the wider network size? Papers that use ARD in other ways to inform network research are also welcome.
 
We invite theoretical, methodological and empirical contributions. Parallel with this session, we will edit a special issue for Social Networks on NSUM and ARD, to appear in 2025. A call for this special issue can be found here: https://www.sciencedirect.com/journal/social-networks/about/call-for-papers#the-network-scale-up-method-and-aggregate-relational-data-in-social-network-research.
 
Zachary Neal
 
Fifty years ago, Breiger (1974) illustrated how a two-mode network representing individuals’ affiliation with groups could be transformed into a one-mode network representing individuals’ associations with each other. His now-classic example focused on 18 womens’ attendance at 14 social events, but two-mode or bipartite projections have since been used to construct networks in a wide range of domains, including co-sponsorship among legislators, co-authorship among researchers, and co-board membership among executives. This session invites empirical papers using projections to study social phenomena, methodological papers developing methods for analyzing projections, and conceptual papers discussing the logic and theory of projections and their underlying duality.
 

Cathleen M. Stuetzer, Stephanie Gaaw, Diesner Jana

 

The use of network research for impact evaluation is a growing area of interest, particularly as organizations and institutions seek to understand the complex interrelations and impacts of their policies, programs, or interventions. Network research involves the study of networks and the patterns of relationships among entities, which can include individuals, groups, organizations, or even countries.
 
Network research provides a rich toolkit for impact evaluation, allowing evaluators to understand not just whether an intervention had an impact, but also how and why it unfolded within the complex web of relationships and interactions that characterize most social, economic, and organizational environments. As with any research method, it requires careful planning, ethical considerations, and an understanding of the limitations and biases that might affect the analysis.
 
This session is dedicated to basic and applied research that brings together network analysis and impact evaluation. We invite submissions from scholars and practitioners that address theoretical, empirical, and methodological approaches to using network analytic methods for impact evaluation. Innovative approaches to network research within the broader area of impact evaluation are also welcome.
 
The session is organized as a set of paper presentations in terms of the number of twenty-minute slots. We expect about 20-50 attendees.
 

Bernie Hogan, Michelle Birkett, Patrick Janulis, Joshua Melville, Kate Banner, Gregory Phillips II

 

Network data collection has often proven to be a challenge, whether through the wrangling of data or the burden to respondents. In the past 20 years, visual methods for data collection have appeared to be one potential solution to respondent burden but may come with their own issues with reliability or setup costs. Within the network community, visual network data collection methods have been prominently featured in recent special issues of Social Networks and Network Science on methodology, ethics, and egocentric data collection.
 
In this session, we invite researchers to present work that speaks to the challenges or opportunities for visual data collection through techniques such as a participant-aided sociogram (e.g., Network Canvas, VennMaker, GENSI). We are seeking presentations that include some insight about the quality or experience of the interview setting as well as those that can speak to the benefits or uses of visual network data collection methods. Such methods are used in a variety of substantive domains from studies of social cohesion to work on public health. This session is not restricted to a specific substantive research domain so long as research insights speak to both the methodological nature of these methods in addition to the mention of insights related to a specific research question or field of inquiry.
 
Through this session we hope to consolidate new insights on network data collection best practices as well as reveal some of the persistent points of tension in the social network data collection workflow that could potentially be addressed through future instrument development and inquiry. While the organisers of the session are members of the Network Canvas team, we welcome users of all visual network data collection methods from pen and paper approaches to novel computer interfaces where the research can help us understand network data collection more fully.
 

Jana Diesner, Andrea Fronzetti Colladon, Peter Gloor, Francesca Greco, Roberto Vestrelli

 

This session is dedicated to innovative research at the nexus of text analysis (including discourse analysis, content analysis, text mining, and natural language processing including deep learning and AI methods) and network analysis/ network science. The study of networks of words, the representation of text-based information as graphs (e.g., knowledge graphs), and the extraction of network data from text data are also topics of interest.
 
Research on “Words and Networks” has led to eminent work, e.g., on language change, recommender systems, collaborative work, semantic computing, text mining for social good, and the diffusion of (mis)information offline and online.
 
Another application domain is organizational communication, where actions meant to support employee communication and client interactions have been developed based on a better understanding of the impact that language has within and across organizations. Furthermore, bringing together text mining and network analysis has been helpful in identifying groups of social agents, resulting in strategies for connecting communities and studying social movements.
 
Another area that combines text analytics with network analysis and network science is the construction of network data based on natural language text data, a process also known as relation extraction. Recent advances with machine learning and artificial intelligence-based solutions that identify relevant entities and relationships between them as they are explicitly or implicitly referred to in text data are also of high interest to this session. Furthermore, methodological innovations, both qualitative and quantitative, for extracting networks from text data, including the construction of multi-mode networks that entail social agents and other entity types, such as resources or information, are also welcome.
 
We invite abstract submissions that contribute to the consolidation of text analysis and network analysis. The papers presented in this session should discuss new methods, applications, or theoretical approaches. We are interested in basic and applied studies.
 
Organizer Contact: Andrea Fronzetti Colladon ([email protected])
 
CONTACT
Heriot-Watt University, Riccarton, Edinburgh, EH14 4AS
[email protected]
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