Conference Proceedings Submissions

Articles

Section default policy

Advancing Measurement Methods for More Accurate and Efficient Network Surveys

Ego-centered and sociometric network surveys are central to understanding social structures, yet they often face constraints such as limited questionnaire time and high respondent burden. This session brings together contributions that advance strategies for making ego- and sociocentric network data collection both more robust and more efficient. 

We invite submissions that explore: 

• Innovative approaches to reducing interview duration, including adaptive and streamlined measurement designs, improved namelist elicitation procedures, and real-time validation techniques that support respondents’ cognitive processes.
• Methodological innovations in ego-network measurement, including new developments in name generators, name interpreters, and approaches for capturing alter–alter relations.
• Technological advances, including novel digital survey modes, graphical elicitation tools, app-based data collection, or multimodal instruments that enhance usability and reduce recall bias.
• Participatory or respondent-centered approaches, including co-developed name generators and interactive feedback mechanisms that increase engagement and improve data accuracy.
• Emerging data sources, including diary-based and high-frequency methods capturing day-to-day contact dynamics, as well as digital communication traces, sensor data, or platform-generated interaction logs that complement or replace traditional network surveys. 

Overall, the session aims to foster dialogue on how methodological, technological, and participatory innovations can jointly enhance the quality and efficiency of network data collection. 

Agent-Based Models of Social Networks

Bridging micro-level mechanisms and macro-social outcomes is pivotal to both Agent-Based Models (ABMs) and social network research. In recent years, a fruitful integration of the two fields has started. ABMs have been successfully applied for theoretical development around micro-level mechanisms and macro-social outcomes in relation to social networks, for the empirical testing of hypothetical causal mechanisms, and exploring counterfactual scenarios that are difficult to test empirically. As a flexible modelling technique, ABMs allow researchers to study the co-evolution of social networks and individual behavior by modelling different tie formation processes and the influence of networks on behavior. Moreover, ABMs allow modelers to incorporate assumptions about actors’ decision-making processes that are cognitively and behaviorally grounded and assess the consequences of changes in those assumptions. Social network effects in an ABM can be calibrated with empirical data, which allows modelers to move beyond the use of abstract networks. In addition, ABMs can be used as a complementary tool to increase the generalizability of statistical analysis of network data. This session invites contributions in these directions, particularly those that attempt to explain macro-social outcomes or the evolution of relational patterns by individual actions and interactions both constrained by and constituting dynamics of social networks. 

Context Sorting and Network Dynamics

This session brings together contributions that investigate how sorting into social contexts—such as schools, workplaces, or neighbourhoods—and the resulting compositional features of those contexts shape network formation and social influences processes. Classical structuralist work has long demonstrated how contextual structures condition opportunities for social interaction (Blau 1977a, Blau 1977b, Blau 1994, Lewis 2015, Skvoretz 1983), but recent advances in network-analytic methods and theories of locally contingent social boundaries, network ecologies, or relational inequalities open up new questions about the interplay between local context and network formation and social influences processes (DiMaggio and Garip 2012, Doehne, McFarland and Moody 2024, Hovestadt and Lorenz 2025, Kroneberg, Kruse and Wimmer 2021, McFarland et al. 2014, Smith et al. 2016, Wimmer and Lewis 2010, Zhao 2023a, Zhao 2023b, Zhao 2025). 

Among the many possible lines of inquiry, we are interested in how features such as the relative size and consolidation of social categories influence both opportunities for interaction and perceptions of social boundaries; whether renewed attention to homophily may obscure deeper sources of segregation that arise before networks form and as a result of individuals selecting into different contexts; and which contextual characteristics foster social influence processes that give rise to the unequal diffusion of ideas and actions. 

We welcome presentations that speak to these or other questions concerning the links between context composition and network dynamics, drawing on diverse methodological approaches and empirical settings such as schools, workplaces, and neighborhoods. 

Criminal Networks

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. 

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. 

Cultural Embeddedness and Social Networks in Tourism

This session explores how cultural embeddedness shapes the formation, structure, and consequences of social networks in tourism. Tourism involves diverse interactions among visitors, residents, organizations, cultural institutions, and digital communities. These relationships are shaped by values, identities, norms, shared meanings, and local contexts. Using social network analysis as a conceptual and methodological framework, the session invites theoretical, empirical, and methodological contributions that examine social, cultural, organizational, emotional, or digital networks within tourism. 

Possible topics include (but are not limited to): 

• Tourist–host interactions and the cultural dynamics of social ties 

• Stakeholder and organizational networks in tourism systems 

• Community and place-based networks shaping tourism experiences 

• Digital, online, and semantic networks influencing destination images 

• Cultural meanings, identity formation, and collective narratives in tourism 

• Innovation, creativity, and collaboration networks in tourism contexts 

• Multimodal or mixed-method network approaches 

The session aims to bring together diverse disciplinary perspectives to advance understanding of how culturally embedded networks influence experiences, interactions, and innovation across tourism contexts worldwide. 

Early and Mid-Career Research in Social Network Analysis: Roundtable Discussion

Social network analysis and network science research communities has grown tremendously in recent decades. This growth in the overall research community also translated into increasing numbers of early- and mid-career researchers (EMCR), such as PhD students and postdocs, in the field. While this situation creates a vibrant research environment, it also creates a job market which may be difficult to navigate for the EMCRs. 

This session is designed as a roundtable with invited guests. Its aim is to support early and mid-career researchers in social network analysis as they navigate the academic grants landscape and research job market. Featuring invited discussants with extensive experience in hiring and mentoring emerging scholars, the session will offer practical advice on critical career stages, from seeking PhD and postdoc positions to landing early-career academic or research roles. 

Key topics include: 

• Identifying strong opportunities and positions in the field 

• Structuring CVs and job applications to highlight relevant skills and experiences 

• Common pitfalls to avoid in applications and interviews 

• Effective preparation for job interviews, including how to demonstrate fit with the institution or research project 

The session will be concluded by open discussion of the discussants with the audience and follow-up networking among the EMCRs. 

This session is organised by Early and Mid-Career Researchers in Social Networks: https://sites.google.com/view/emcrs-social-networks. 

Families as Networks

For many people, family ties are among the most important personal relationships and last throughout their lives. People end relationships with romantic partners and friends. However, family ties cannot be ended in the same way: even if one moves away or if a relationship is troubled, a brother is still called a brother. 

Demographic processes, such as increased life expectancy, lower fertility, and increasing family complexity, are changing the size and structure of our family networks. Moreover, technological and social developments have changed the ways we communicate with our family members. Furthermore, friends may take over functions formerly fulfilled by the family if family members do not live nearby. 

In the handbook Family as Networks, we propose that considering the family as a complex and dynamic network of relationships is a fruitful way to address and understand the heterogeneity and complexity of family relationships. The session Families as Networks is organised in light of this forthcoming handbook, which is expected to be released by the end of the year. All contributing authors are invited to present their chapters at the conference. Moreover, researchers studying families as networks who are not contributing to the handbook are also invited to present their work. 

Global Perspectives on Personal Networks: Data Sources, Case Studies, and Cross-Cultural Comparisons 

Over the past few decades, an increasing number of surveys on personal networks have been conducted. However, with a few exceptions, these studies are often limited to national contexts or specialized samples. In this session, we aim to bring together presentations that focus on international or cross-cultural comparisons of personal networks, leveraging the cumulative nature of these studies to uncover large-scale patterns and insights. Contributions may explore data collection methods (Qualitative approaches, Surveys, Social Media data), theoretical frameworks that may account for the nature of personal network data, or comparative studies, among others. 

Intergroup Relations in Social Networks

There is growing interest in social network analysis to better understand intergroup relations across many disciplines. Using ego-centered and whole network data, both cross-sectional and longitudinal network studies have established that social networks are segregated along ethnic, cultural, and religious lines. 

In recent years, we have seen exciting new applications of social network analysis that have improved our understanding of the processes underlying the emergence of intra- and intergroup relations and their consequences, 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 causes and consequences of intergroup relations in social networks. 

Longitudinal Network Modeling

Important insights into social networks can be obtained with the help of longitudinal observation designs. Such designs can be of a varied nature. Panel designs are traditionally used to collect self-reported networks by questionnaires; regular time series and time-stamped data can be obtained from official records or automated data collection tools (trackers, apps); 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. Papers can have a mathematical, statistical, theoretical, or empirical subject-matter focus, as long as they are relevant for empirical social science. 

Micro-Level Determinants of Network Structure Characteristics

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 has 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 examine how micro-level selection processes shape macro-level network structures. We are particularly interested in studies that explain specific structural characteristics (e.g., clustering, segregation, cohesion) through micro- or meso-level behaviors or mechanisms. Empirical, theoretical, and methodological contributions are all welcome. 

Mixed Methods for Social Network Analysis

Social network researchers increasingly use different tools, methods, and methodological perspectives within their projects, a trend seen across many disciplines. This trend is partly associated with the excellent connectivity of knowledge and the rise of open access. Mixed methods approaches allow scholars to obtain shared concepts to make their studies dialogue with each other and also provide a deep understanding of the social phenomena under investigation. Multiple authors have employed mixed methods embedded with a social network perspective (e.g., Bellotti, 2015; Edwards, 2010; Froehlich, Rehm and Rienties, 2020; Hollstein & Dominguez, 2014; Ortiz, 2022; Small, 2011; Verd, 2008), highlighting both opportunities and challenges. In this organised session, we welcome presentations using a mixed methods approach for social network analysis, which can be empirical or methodological. Empirical papers could, for instance, highlight the rationality behind their specific approach to mixing methods, and the opportunities and challenges they faced (e.g., ethical, methodological, theoretical, triangulation, open access data). Methodological papers could propose new tools and software, test assumptions in previous mixed-methods research, or provide a review of previous studies. The session aims to give attendants a good grasp of the state of the art of mixed methods research in social networks. 

Modeling Social Influence

The theme of peer effects and social influence plays a role in much of social network research. Empirical studies of influence processes using longitudinal network-and-behavior designs are today common in many social sciences disciplines. Increased availability of suitable methods, software, and datasets has also led to deeper and more extensive research questions. A large portion of network research in this area has been about peer influence, often applied to adolescents’ friendship networks, where a basic question is to distinguish between peer influence and peer selection. There are a lot of other topics concerned with influence. In organizational sociology, influence based on positional equivalence has been advanced as a theoretically better justifiable mechanism than influence based on direct connections. Also who influences whom in a network is still a very open question in many research domains. From a more abstract perspective, influence is not restricted to network-and-behavior studies. There also is a wide variety of network-network influence patterns, where one network defines who influences whom, and the other network defines what content is transferred by the influence. Examples can be found in co-evolution studies of several one-mode networks (e.g., friendship and bullying), but also in studies where a one-mode network (e.g., advice-seeking among students) co-evolves with a two-mode network (e.g. sports activities the students engage in). 

This session will be open to methodological, theoretical, and empirical studies of influence in social networks. Papers can be mathematical, statistical, theoretical, and/or empirical in their focus, as long as they are relevant for empirical social science. 

Networks and Sustainability

Sustainability is a multidimensional concept encompassing the co-existence of human and natural systems within planetary boundaries, the development of ecosystem-aligned social practices, and a growing awareness of the 17 UN Sustainable Development Goals. Whether in resource management, climate mitigation, or the adoption of green technologies, the interaction between human behavior and the environment is inherently networked and best understood through network processes. 

Building on two successful panels at recent SUNBELT conferences, we aim to provide a forum for researchers applying network approaches to sustainability. We seek a wide range of contributions that tackle sustainability challenges, including, but not limited to, socio-ecological resilience, transitions to low-carbon systems, governance and coordination challenges across sectors and scales, and the societal diffusion of environmental norms and practices.  

The session embraces the diversity of network methodologies - from quantitative to qualitative, including modeling - but also the interdisciplinary nature of research at the intersection of networks and sustainability. We therefore invite submissions from anyone applying network perspectives to sustainability topics, fostering a dialogue across disciplines to lay the foundations for future research in this increasingly vital area. 

Networks of Weak Ties and Social Cohesion

Strangers can be consequential (Blau & Fingerman 2009). Talks in this session explore the structure and function of weak ties, acquaintanceship relations, casual contacts, or infrequent social connections. Such socially-distant connections can facilitate information flow, support collective action, or bridge otherwise disconnected communities. In this way, contributing to (the lack of) social cohesion, integration or inequality. At the same time, they are opportunities for forming stronger social relationships. 

We invite contributions that investigate both the determinants and societal consequences of configurations of acquaintanceship networks and other forms of low-intensity or infrequent social connections. Why and how do these networks emerge? Which individual, contextual, or structural conditions shape their size, diversity, stability, or bridging capacity? And how do these configurations influence trust, cooperation, political behavior, fragmentation, or broader patterns of cohesion and conflict? 

The session is open to theoretical, empirical, and methodological contributions. We particularly encourage research advancing the measurement and modeling of socially distant ties, including innovations in survey instruments and name generators, large-scale or multi-layer network data, simulation-based approaches, relational inference methods, network scale-up techniques, and computational tools for analyzing sparse or partially observed networks. 

Personal Networks across the Life Course

Personal networks and life-course scholarships have become increasingly intertwined in recent years. A strong interest in personal networks has developed in life course research around the theme of linked lives, stressing the relational dimension of any personal trajectory. From birth to death, lives link and unlink, intentionally or inadvertently, due to changes in individual lives or resources. Likewise, scholars initially focused on family and peer networks have become increasingly aware of the importance of unfolding relationships over time, along with life events, transitions, and trajectories, shaping the structures and dynamics of such networks. To further integrate the two lines of research, we propose a session on personal networks from a life-course perspective.  

Papers on the interrelations between life events, transitions, and personal networks are welcome. Such events, whether expected or unexpected, often have consequences for personal networks, which may accumulate into trajectories of cumulative advantages/disadvantages. Conversely, individuals actively shape their networks to cope with challenging transitions. How and through which processes are trajectories related to individual growth and development, in providing security and comfort and a sense of belonging, and in shaping one’s life chances and identity? The associations and causal mechanisms linking personal networks and individual well-being in general and across several life domains are also of interest, as are the importance of negative and ambivalent ties for life-course issues, and the unfolding of dormant relations and relational unlinking mechanisms. Papers with a longitudinal design are encouraged, although other designs are welcome. Quantitative, qualitative or mixed approaches are equally welcome. 

Political Networks

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). 

Population-Scale Social Network Analysis

The analysis of large-scale societal networks has recently seen tremendous growth, in part because of the relative abundance of digital data sources such as online social networks or mobile communication datasets. However, most of these data sources lack demographic data on users, or contain uncertainties with respect to the representativity of the user sample. Moreover, it is often not clear what exact social relations these online or communication ties represent, therefore, it is difficult to interpret findings. 

Population-scale social networks can largely overcome these drawbacks, because they are derived from highly curated official data sources. Since national digital registers by definition include every resident of a country, the boundaries of the network are precisely defined. In addition, rich demographic and socio-economic attributes on the nodes are also available alongside the network structure. Moreover, because relationships between people are derived based on family registers, tax data, employment and school affiliations, we also precisely know the type of each relationship. Methodologically, social ties defined this way are fundamentally different from online social ties or communication ties, and the scale of the data in itself might presents various methodological problems. Apart from discussing a novel line of research, the session audience is expected to be as diverse as the general audience at EUSN, featuring social scientists, statisticians, physicists, demographers, economists and computer scientists. 

Given that this data has recently become available in several countries, including the Netherlands, Denmark, Sweden, Finland and Austria, more than sufficient interest in this topic can be expected at EUSN 2026. 

Scientific Collaboration Networks: Data Collection and Quality, Methods, Models, and Empirical Application

Scientific collaboration networks are a primary lens for understanding socio-cognitive ties, revealing the mechanisms behind scientific inequalities, the formation of morphological structures (such as invisible colleges or paradigmatic groups), and the dynamics of knowledge production. Besides traditional research, which has often relied on formal communication channels such as co-authorship, citations, or supervision as proxies for social ties, there is a growing need to capture the informal and complex dynamics of scientific interaction. This panel seeks to complement standard bibliometrics by adopting a comprehensive social network approach.  We aim to integrate classical social science methods (e.g., surveys, ethnographies) with sophisticated large-scale datasets (e.g., Web of Science, Dimensions, OpenAlex) to examine the inner workings of science. We invite contributions that discuss data quality, collection strategies, and novel methodological models for analysing the structure and evolution of collaboration. We welcome empirical applications addressing topics such as: 

• The interplay between local and global scientific networks. 

• Policy-driven changes in collaboration patterns. 

• The influence of political shifts on science and knowledge production. 

• The role of consortia and collaboration in addressing global challenges. 

Social Isolation and Loneliness

There has been an increased concern about the prevalence of loneliness, which is well reflected in the recent publication of concise reports by international organisations, like the WHO and OECD, as well as a growing interest in the subject by the EU as well. These reports all distinguish the objective side of social disconnection, that is, social isolation, and the subjective side, feeling lonely, but also call attention to the fact that studies apply various definitions and measurements which make it difficult to present reliable international comparisons and identify temporal trends.  These two problems are interrelated, but are definitely not identical: they are caused by different factors and may have differing consequences as well. The session aims to bring together scholars interested in and researching the interrelatedness and/or longitudinal changes of these two phenomena. Both qualitative and quantitative approaches are welcome. 

Social Network Data Quality

While data quality has been extensively studied for traditional social science survey data, for social networks data quality needs to be considered from a different angle. Relations are social networks’ biggest strength, but interdependence induces restrictions in model applicability and data quality assessment. As traditional independence assumptions, which are the gold standard for most non-relational data in the social sciences, do not hold for social networks, many existing data quality frameworks cannot be applied. Every new research process begins with questions relevant to data quality, like use-case selection, boundary specification and construct validity, i.e. how to accurately measure what nodes and ties are. Further data quality considerations include strategies that try to avoid measurement error while the study is in the field. They also encompass data completeness, sampling error, and biases researchers can introduce when postprocessing the data they or others collected. 

This session focuses on advances in social network data treatment that assess errors and biases in network data or suggest strategies to measure their extent or to mitigate their consequences. We invite empirical and theoretical contributions using network data collected via surveys, observation, digital or linked data types. 

Social Networks and Health

People's health is actively shaped by their social networks in multiple ways. Most directly, through infectious conditions that spread through social contacts, but also through the availability of social support and provision of health-related knowledge, attitudes and behaviours. We thus invite abstracts that consider either how social support (i.e., who provides what to you and what flows through ties) and social context (i.e., where you fit within social structures and how social space assists or limits) impacts their health. Papers within scope would include consideration of either how health affects network characteristics, or how networks affect health - including health knowledge, behaviour and outcomes. We welcome both ego-centric and whole network approaches so long as they address the interplay between individuals’ health and networks. In previous iterations of this session, health topics have included substance use, sexual health, mental health and non-communicable health conditions – but other areas of research are welcome. Quantitative, qualitative and mixed-method approaches are all welcome. 

Social Networks and Health Behaviors

Social network perspectives have long helped explain how health behaviours spread and how inequalities emerge. As technologies (e.g., social media) and novel products (e.g., e-cigarettes and nicotine pouches) evolve, these social network theories need to be enriched and revised to reflect those changes which can have a potential impact on the prevalence of health behaviours as well as related inequalities (Huang et al., 2014; Kisfalusi et al., 2020; Piombo et al., 2025; Radó et al., 2024). This session invites empirical, theoretical, and methodological contributions that use network approaches to advance understanding of health behaviors (e.g., stress coping, alcohol use) and inequalities in those. We welcome studies that examine peer selection and influence, co-evolution of networks and behaviors, multiplex (online/offline) networks, and nicotine-related health inequality across social groups using survey data or administrative register data (Radó et al., 2024, 2026). Contributions addressing network measurement challenges, innovative data sources, and causal inference are encouraged (Salvatore et al., 2024; Steglich et al., 2010). We also invite work that informs the design, implementation, or evaluation of network-based interventions aimed at reducing the prevalence of nicotine product use (Lakon et al., 2025; Valente, 2012). 

Social-Based Optimization Algorithms

This session examines Socially Based Optimization Algorithms (SBOA) and their applications in modeling complex digital societies. As a subtopic, it introduces the Post-Truth Optimization Algorithm (PTOA), an innovative variant designed to simulate the propagation of subjective knowledge, belief dynamics, and influence in network systems. PTOA combines social network theory with control engineering, computational modeling, and technopolitical analysis to provide a quantitative framework for examining technopolitical interactions and decision-making processes under "post-truth conditions." 

This session, which integrates theoretical and practical approaches to understanding socially based optimization algotihms, network dynamics, and the socio-technical mechanisms that shape collective behavior, is invited to present empirical or computational work. This session aims to foster interdisciplinary work by combining experiences from engineering, computational social sciences, and sociological theory to address challenges in digital societies influenced by information perception, social influence, and technopolitical factors. 

Statistical Methods for Network Dynamics

Recent decades have witnessed rapid development in statistical methods for modeling and understanding network dynamics. This session highlights new statistical methods for social network analysis, focusing on the development and advanced applications of statistical models designed to explain the structure and dynamics of social networks.  Contributions may address models for cross-sectional, longitudinal, or time-stamped networks, and may consider a variety of tie types, including dichotomous, weighted, signed, or multiplex relations, and hypergraphs. Contributions on statistical models for dynamics on networks, including methods for network-attribute co-evolution and cross-sectional social influence analysis, are also welcome. We welcome submissions that present novel methodological advancements, particularly those that include an empirical illustration, and applications of innovative methodology. By bringing together quantitative methodologists and substantive researchers, this session aims to foster dialogue around rigorous inference, computational efficiency, and model interpretability in the study of dynamic social structures. 

Stochastic Actor-Oriented Models for Longitudinal Networks

A book with the title “Stochastic Actor-Oriented Models for Longitudinal Networks” will be published in 2026 by Cambridge University Press. The authors are the organizers of this session. The session will be devoted to highlighting the book, and there will be presentations about some new topics that were not fully treated in earlier publications. 

Open Submission

Choose this session if you are not yet sure where your submission would fit. However, please attempt to find a fitting submission first. We will try to place submissions from this session into appropriate slots where possible, but direct submissions to the session will get precedence.

Poster Session

Submit your abstract to this session if you wish to present your work as a poster.