Giancarlo G. Ragozini, University of Naples Federico II (giragoz@unina.it)
Matteo Magnani, Uppsala University
Roberto Interdonato, CIRAD
Maria Prosperina Vitale, University of Salerno
Giuseppe Giordano, University of Salerno

In recent years it has become more and more frequent to use network models going beyond simple directed/undirected and weighted/unweighted networks, to capture the complexity of old and new fields of application of network analysis. Multilayer networks are an example of such models, extending graphs with the concept of layer, that allows us to represent a multitude of scenarios from the different types of ties we find in a multiplex network, to different types of actors, to different temporal snapshots of the relations between the same group of actors. Multilayer network models can themselves be enriched with additional features, such as attributes and edge probabilities, with the aim of describing real phenomena in more detail.

Multilayer and feature-rich networks allow us to introduce new research questions (and corresponding social network analysis measures and methods). For example, instead of asking how central an actor is, we can focus on the role of the different layers in determining the centrality of the actors. Second, existing social network analysis concepts do not always have a clear corresponding extension in complex networks. For example, it is still unclear how communities spanning multiple layers should look like, or how different features should contribute to the definition of communities, or how to effectively visualise multilayer and feature-rich networks, e.g. layers, features or modes, in the same sociogram. In addition, multilayer networks allow to use multiple types of layers (e.g., in temporal multiplex networks), which requires the joint application of methods developed for simpler models (e.g., only temporal, or only multiplex).

This session focuses on recent advances in the analysis of multilayer and feature-rich networks, either in terms of new research questions, or new methods, or new applications. More specifically, topics for this session include but are not limited to:

• New models for multilayer and feature-rich networks, or comparison of alternative models;
• Measures for multilayer and feature-rich network;
• Community discovery in multilayer and feature-rich networks;
• Multilayer and feature-rich network embedding;
• Visualisation of multilayer and feature-rich network;
• Multilayer and feature-rich network simplification (e.g., sampling, filtering, flattening, projections);
• Applications;
• Software.

Giancarlo G. Ragozini, University of Naples Federico II (giragoz@unina.it)
Maria Prosperina Vitale, University of Salerno
Giuseppe Giordano, University of Salerno

Collaboration networks attract a lot of attention in many scientific domains. The session focuses on presenting methodological developments and novel applications related to the session topics.

Special interest is on the analysis of collaboration networks in presence of complex data structure, and on collaboration data extraction and empirical data collection.

The organizers solicit the submission of abstracts dealing with the following topics:

• Academic and scientific networks;
• Analysis of collaboration networks in economics, cultural and social environments;
• Co-authorship networks;
• Collaborative innovation networks;
• Community detection in collaboration networks;
• Dynamics and evolution patterns of collaboration networks;
• Empirical data collection;
• Mixed methods for data collection and data analysis.

Hetty Wenxian Sun, Greenwich Business School (w.sun@gre.ac.uk)
Petros Ieromonachou, University of Greenwich
Aaron Tan, University of Greenwich

As a network, ecosystems are present and thriving in the world in various forms. This track looks specifically at entrepreneurial ecosystems which relies on people, the culture they bring in and the way they interact with each other. People, as one of the most central parts to support entrepreneurial ecosystems, plays many different roles: policymakers, lawyers, community leaders, investors and so on, and indeed, “entrepreneurship is a community sport” (Whitters, 2014). Great businesses are built by great people, and without high-skilled workers, they would not have surfaced. To continuously supply the entrepreneurial talent, the ecosystem would need to attract, engage and nurture people, especially young people, with skills that could allow them to be more responsive to the business requirements.

A diverse culture is the fertilised soil for ecosystems, which enables the production of a broad range of entrepreneurial solutions to issues present in the world and society. This leads to initiatives to solve wider problems such as climate change, global warming and personal security, as well as reducing the unemployment rate, improving public services and boosting mental health. A diverse team often brings in better results (Rock & Grant, 2016) and hence truly drives the growth of the ecosystem. Economic progress is the result of innovations (Holcombe, 2007) and market share is constantly taken by new businesses and ideas. An ecosystem should allow entrepreneurs to experiment with new business models and technologies to achieve growth and during which, plenty of interactions among entrepreneurs, policymakers, investors and competitors will provide a rich context for social network analysis.

Sample topics
The EU Social Networks Conference Ecosystem of Entrepreneur track encourages and welcomes researchers who recognise the difference of ecosystem elements and take particular interest in examining their interactions in the entrepreneurial world contributing to the following themes (but not limited to):

• Cultivate ecosystem
• Cultural and interactive aspects of relationship with policymaker
• Human capital in the entrepreneurial ecosystem
• Building community capacity for ecosystem development
• Entrepreneurship education from an ecosystem perspective
• Millennial entrepreneur and talent
• Innovation-driven entrepreneurship ecosystem
• The role of open innovation
• Investment ecosystem for start-ups
• Global ecosystem from a financial and technological perspective
• Competition and cooperation in entrepreneurial ecosystems

Vera de Bel, University of Turku, Netherlands Interdisciplinary Demographic Institute (vera.debel@utu.fi)
Thomas Leopold, University of Cologne
Marlène Sapin, LIVES & FORS, University of Lausanne
Eric Widmer, LIVES, University of Geneva

Life-course trajectories and transitions are intertwined within the complex webs 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, do not only exert a positive influence on the individual members of the network. Family and personal networks may also cause stress or strain on the individual and the network level. In addition, family and personal networks change over time, which may have consequences on the access to resources and may for example affect individual network members’ well-being, behaviour, and life chances.

This session invites papers on personal and family networks during the different stages of the life course. Papers focusing on the transition into adulthood, family formation, union dissolution, transition to retirement, and ageing are encouraged to be submitted, but studies on other life-course changes are also welcome. Quantitative as well as case studies on specific normative or non-normative life events are also of interest to this session.

Stefano Ghinoi, University of Greenwich (s.ghinoi@greenwich.ac.uk)
Guido Conaldi, University of Greenwich

This session will be dedicated to the exploration and discussion of novel methodological approaches and software applications for the analysis of social networks. The session aims to bring together theoretical contributions, empirical applications, and software illustrations using novel analytical tools - especially in cases where a more specialised organised session is not also offered. Topics for this session include, but are not limited to:

• Advancements in agent-based modeling;
• Advancements in blockmodeling;
• Community detection and graph partitioning;
• Developments in – or entirely new - descriptive network measures
• Software developments for the visualisation and analysis of networks

This list is not exhaustive, and the topics are provided as examples. We encourage submissions of a wide range of topics related to the general aim of the session.

Nynke Niezink, Carnegie Mellon University (nniezink@andrew.cmu.edu)
Robert W Krause, Free University Berlin

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. Papers can have a mathematical, statistical, theoretical, or empirical subject-matter focus, as long as they are relevant for empirical social science.

Keywords: network dynamics, longitudinal networks, actor-oriented models, network event models, Dynam, LERGM, TERGM, Siena, relevent, goldfish.

Andras Voros, University of Manchester (andras.voros@manchester.ac.uk)
Zsófia Boda, University of Essex
Elisa Bellotti, University of Manchester

The importance of multiplexity is increasingly recognised in (educational) network research. While research into the effects of peer networks has traditionally focused on a single network dimension at a time, most commonly on friendship, this approach has been shifting lately.

A wave of studies in recent years has showed how multiple forms of social ties emerge between students and affect a variety of their outcomes. Relevant networks include personal relations such as liking or “friendly” ties, spending free-time together, studying together, dislike, conflict, victimisation, and romantic ties. Besides these, interpersonal perceptions appear to have an impact on student behaviour and outcomes as well: such as perceptions about the status, social roles, or personality of peers.

Longitudinal studies have demonstrated that the emergence and change of the various network dimensions is interconnected. Multiplex social networks jointly influence individual outcomes, such as academic achievement, school attitudes, mental and physical health, political attitudes, and so on.

This section invites presentations which explore the importance of multiplex networks for individual outcomes in educational settings.

Particularly (but not exclusively), we would be happy to hear about work that focuses on:

• Data collection techniques for multiplex networks in school;
• Statistical methods that are specific to multiplex networks in school;
• Empirical data analyses and results involving the evolution of multiplex networks in school;
• Empirical data analyses and results involving the relationship of multiplex networks and individual outcomes in school.

The list is not exhaustive: we are very much open to a wide range of studies on the topic of multiplexity in schools. We hope to bring together a diverse set of research projects and facilitate discussion and collaboration between scholars interested in educational network research.

Stefano Ghinoi, University of Greenwich (s.ghinoi@greenwich.ac.uk)
Guido Conaldi, University of Greenwich

The use of network analysis in bibliometrics has a long tradition, which dates back to the 1960s. However, while the analysis of bibliometric networks has become extremely popular in the last decades, there are still some areas that have received less attention; in particular, the construction of bibliometric networks, the use of different data sources, and the impact of bibliometric methods. Moreover, novel research topics constantly emerge in different scientific disciplines, and their evolution requires a robust mapping process.

This session is dedicated to methodological advancements, empirical applications, and proposals on the use of novel software and tools for applying network analysis in bibliometric studies. We welcome contributions exploiting the role of network analysis in bibliometric studies, including (but not limited to):

• Network structures in bibliometric studies;
• Authors’ and papers’ centrality;
• Co-authorship, co-occurrence, and network metrics;
• Modularity, sub-groups, and clusters;
• Cross-country collaborations;
• Bibliographic database journal coverage;
• Editorial board networks;
• Actors’ attributes in scientometrics;
• Network visualization.

Lucio Palazzo, University of Naples Federico II (lucio.palazzo@unina.it)
Roberto Rondinelli, University of Naples Federico II
Filipe Manuel Clemente, Viana do Castelo Polytechnic Institute
Kristijan Breznik, International School for Social and Business Studies
Riccardo Ievoli, University of Ferrara

The analysis of sport data is becoming truly helpful for recognizing the strengths and weaknesses of individual players and collective behaviors of teams. Using such information is possible to make better decisions and organize the strategy to achieve greater success both in terms of sport results and economic aspects. Therefore, the rise of sport analytics tools mixed with the availability of data allow the spread of innovative methodologies in a broad range of sports. In this context, relational data are also arising.

The proposed session focuses on contributions regarding network analysis in sport data. Between the possible topics, network analysis may help to unveil the key elements regarding tactics and/or team strategies in team sports. Furthermore, connections between teams (e.g. trading and exchanges) and/or federations cover an important role and may contribute to sport results. The search of appropriate methodologies to deal with those data remains an open issue.

The audience of interest may include experts in statistics, operations research, machine learning, scientific computing, economics, sports management, and sport science interested in expanding these topics in a network perspective. Audience members will become aware of the most current thinking on common problems of interest in network modeling or analysis of sports data.

The session welcomes empirical, methodological and/or theoretical contributions exploiting the role of Network Analysis in sports, including (but not limited to):

• Local network structures;
• Temporal networks;
• Network indicators and sport outcomes;
• Signed networks;
• Multimodal networks;
• Multilayer networks;
• Complex networks.

Innovative approaches of network analysis for popular team sports (e.g., football, basketball, and volleyball) as well as original applications based on less known sports are also welcome.

Paolo Cimadomo, University of Haifa (cimadomopaolo@gmail.com)
Anna Collar, University of Southampton
Maria Carmela Schisani, University of Naples Federico II

The network perspective has currently reached a paradigmatic position in some fields, like sociology. Moreover, during recent years we have seen a steady increase of publications and works on a number of economic, social, cultural and religious aspects that have attempted to apply network analysis to the past world, in particular to explain their interconnections. Network analysis attracted scholars of human past for their potential in investigating human relationships, visualising and exploring their structures among different archaeological and historical sources. Archaeological and historical data sources pose challenging opportunities to network analysts and network scientists. World-Systems Analysis has especially emphasized the importance of understanding interactions and interrelationships between different peoples or inside the same human group.

The aim of this session is twofold. Firstly, we want to work towards a specific historical and archaeological network analysis, drawing on the relational thinking of network theory and incorporating archaeological and historical sources critique and reasoning. Secondly, we want to present new findings and approaches within historical and archaeological network research, and promote contacts between the various disciplines that approach past phenomena using methods derived from network analysis or network science.

The session invites contributions from various disciplines applying the methods of formal network analysis and network science to the study of the historical research. The contributions will answer questions such as: how can we detect change in human networks change over a long timeframe? How can literary and historical sources and material culture help in answering this question?

We welcome submissions about any period, geographical area and topic, which might include but are not limited to: economics, politics, military issues, religion and science, interpersonal relations, kinship, cultural networks, artistic transmission, material and immaterial connections, migration, networks extracted from texts, geospatial or temporal networks, big data and data collection from fragmentated sources.

Tomáš Diviák, University of Manchester (tomas.diviak@manchester.ac.uk)
Paolo Campana, University of Cambridge

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, criminal networks, terrorist networks.

Spyros Angelopoulos, Durham University (spyros.angelopoulos@durham.ac.uk)
Emmanuel Lazega, SciencesPo
Francesca Pallotti, University of Greenwich
Paola Zappa, Maynooth University

The networked nature of organizations, and the organizational contexts of network dynamics create a complex ecosystem where individuals, groups, units, and other organizations are entangled and recursively active. Such 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, and implications of the cross-level processes leading to the emergence of relations and outcomes at various levels. Submissions can refer, but are not limited, to the following areas of research:

• Micro-foundations of organizational networks: how individual characteristics and cognition 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.

We welcome both theoretical and empirical contributions addressing various aspects and implications of organizational networks research.

Dimitris Christopoulos, Modul University Vienna
Manuel Fischer, University of Bern
Christina Prell, University of Groeningen
James Hollway, Graduate Institute, Geneva)
Petr Ocelik, Masaryk University (petr.ocelik@gmail.com)

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 behaviour 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).

Eszter Bokanyi, UvA (e.bokanyi@uva.nl)
Laszlo Lorincz, Corvinus Universtiy
Guilherme K. Chihaya, Umeå University
Frank Takes, Leiden University
Eelke Heemskerk, University of Amsterdam

Multiple countries set up digital infrastructures to utilize citizen registers for academic research purposes. Recent technological advances make it possible to use these registers as rich resources for population-scale social network analysis by deriving formal ties of people based on, e.g., family, education or employment data. It enables new exciting research of relations at an unprecedented, representative scale, leading to actionable insights into key issues such as segregation, social change, or inequality. This fits in well with EUSN’s goal of providing a platform for the exchange of ideas on social network research. Discussing this novel branch of large-scale social networks, their potentials and limitations with respect to existing methods will likely be beneficial for participants of EUSN.

Philip Leifeld, University of Essex (philip.leifeld@essex.ac.uk)

Networks of political actors, such as legislators, interest groups, charities, NGOs, firms, political parties, and government agencies and branches, play a pivotal role in the policy process. They influence agenda setting, engender policy change or promote policy stability, act as backbones of polycentric or multi-level governance systems, and they can vary across institutional settings. In the literature, a variety of networks in public policy has been analysed, including discourse networks/policy debates, information exchange or collaboration among political actors, social media interactions, staff exchange, reputational networks, issue networks, lobbying relationships, and membership in organisations or forums. Policy and discourse networks can produce consequential structures, such as polarised advocacy coalitions, central brokers or opinion leaders, or polycentric clusters.

This panel invites submissions about applications of network analysis to the study of public policy, applications of discourse network analysis, the intersection between discourse and policy networks, the study of lobbying and interest groups, methodological contributions to the study of policy or discourse networks, and comparisons of networks across institutions, topics, data sources, or relations.

Srinidhi Vasudevan, University of Greenwich (srinidhi.vasudevan@greenwich.ac.uk)
Anna Piazza, University College London
Madeline Carr, University College London

Building on cyber security that specifically focuses on machines and technology, social cyber security is an emerging and interdisciplinary field with perspectives from sociology, communication science, forensics, economics, linguistics, social psychology, and political science to name a few. Social cyber security looks at people, processes and technologies and the interactions between them to identify the influences impacting security behaviours of actors. Social Network Analysis provides a relational approach to provide a context for the creation and maintenance of social relations. Networks are embedded in cyber norms, cultures, values, and behaviours which for instance can vary according to contexts. For instance, cyber information sharing networks can differ across industries and countries, cyber behaviour can be influenced not only by organisational culture and norms but also by the patterns of social interactions among individuals within the organisations, criminal gangs on the Dark Web manipulated by ringleaders and the network topologies, cyber investments determined by interactions between the organisation’s risk appetite and its environment etc. This organized session brings together research that addresses these and related questions through a broad, cyber-network perspective.

To develop ‘social cybersecurity’ as a framework, we solicit methodological, conceptual, and empirical contributions that model, predict, and/or explain how social ties that are created and maintained by actors in a digital environment.

Topics of interest include but are not limited to the following lines of enquiry:

• Organised crimes, forensics, criminal behaviour;
• Cyber user behaviour and networks;
• Diffusion, misinformation, and disinformation;
• Mental health of cyber practitioners;
• Information sharing networks in cyber;
• Governance structure and cyber policy;
• Data science, machine learning, natural language processing and agent-based simulation in cyber space;
• Contexts of tie creation, maintenance, and dissolution in cyber space;
• Organisation and industry pertaining to cyber investment and policy.

Andras Voros, University of Manchester (andras.voros@manchester.ac.uk)
Zsófia Boda, University of Essex

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.

Kim Bui, University of Greenwich
Pi-Chi Chen, University of Greenwich
Bruce Cronin, University of Greenwich (c.b.cronin@gre.ac.uk)
Lena Langosch, University of Greenwich

Networks are a central concept in the study of International Business (IB) from supply and value chains to parent-subsidiary relationships and the embeddeness of multinational subsidiaries in host country environments. A core perspective in IB research is the use of a network lens through which firms are conceptualized as “embedded in social networks with other actors” (Andersson, Forsgren, & Holm, 2002; Granovetter, 1985). But while the theory of networks has attracted increasing attention in IB research, the systematic description, modelling and analysis of network relationships has still been scarce in IB research (Kurt & Kurt, 2020). Few studies of international business networks take the concept beyond metaphor.

Social network analysis (SNA) provides a rich set of mixed methods ability to provide contextual, longitudinal, multilevel, and processual explanations of International Business phenomena (Buchnea & Elsahn, 2022). As such, the incorporation of SNA and IB can be used to understand the path-dependent process of network development and change over time, and the implications of network embeddedness for firms’ behaviour and strategies. This conference track aims not only to incorporate theory of networks in IB research, but also recognise and highlight outstanding use of SNA to investigate pertinent IB phenomena.

The track therefore seeks to showcase rigorous and trustworthy use of SNA in IB research and question methodological conventions in SNA and IB and promote cutting-edge developments in SNA and IB methodological approaches. The EU Social Networks Conference Social Network Analysis and International Business track welcomes high quality submissions in the form of conceptual and empirical papers that develop new perspectives on SNA in IB that fit the 21st century global landscape. Studies employing a SNA perspective have enriched the understanding of international business, suggested areas of interest include (but not limited to) the following:

• Application of SNA in the speed and characteristics of internationalisation of multinational enterprises (MNEs) (Musteen et al., 2010).
• Knowledge exchange and transfer and learning within and outside of MNEs, including HQ- subsidiary relationships (Geppert & Dörrenbächer, 2014; Sandberg, 2014; Khan, Rao-Nicholson & Tarba, 2018).
• Types of cross-border relationships (Holm et al., 1996, Pedersen et al., 2019).
• Entrepreneurship (Coviello, 2006) and Internationalization of SMEs (Chetty & Holm, 2000).
• Exploration on how businesses interact with its environments (Welch & Wilkinson, 2004; Jansson, Johansson & Ramström, 2007).
• Corporate political activity and how firms manage the socio-political environment (Elsahn & Benson-Rea, 2018).

Further suggested questions and areas of interest include the following:

• What network theories can we develop to address new challenges in IB?
• How can we adapt SNA methods for today’s IB research challenges?
• How can SNA account for the dynamism and temporality of IB phenomena?

Emily Long, University of Glasgow
Claudia Zucca, Tilburg University (c.zucca@tilburguniversity.edu)
Mark McCann, University of Glasgow

Many of the problems that researchers and practitioners face every day addressing social, economic, political, and health issues are complex. A complex problem is characterized by the unpredictability of an outcome when we intervene in the system. For instance, promoting a policy to provide jobs for people who are unemployed, while not considering the many reasons they may be unemployed in the first place. In order to address complex problems, the field of system science employs a range of methodologies to intervene in complex systems and produce outcomes that are good for society. Social Network Analysis is one of the methods in the system science toolkit, alongside complementary methods such as agent-based modelling, System Dynamics, system thinking, etc.

This session will bring together scholars from social network analysis and system science to discuss research aimed at understanding complex systems where variables are intertwined, and outcomes are non-linear. We welcome studies that combine other system science approaches to network analysis, for instance, ABM simulations of social networks or semantic networks derived from causal loop diagrams. Both qualitative and quantitative research is welcome.

We are particularly interested in hearing from colleagues whose work is aimed at social change – researchers who collaborate with stakeholders in social, political, economic and health science. For instance, research that addresses problems such as adopting policies, the impact of new laws, effects of inflation, comorbidity of diseases, and the implication of loneliness for young people would be a good fit for this panel.

Raffaele Vacca, University of Milan (raffaele.vacca@unimi.it)
Başak Bilecen, University of Groningen

Migration scholars have long called attention to the central role of social and personal networks in shaping migrants’ mobility patterns, migration decisions, incorporation trajectories, and transnational activities. However, while certain network metaphors and notions have always been popular in migration research, the actual collection and analysis of network data has been far less common in this field. A recent special issue of Social Networks showcased the potential of network data and methods, both egocentric and sociocentric, to answer different and fundamental questions in migration studies. This recurring EUSN/Sunbelt session aims to highlight the richness and variety of social network studies of migration and migrant incorporation, and their ability to open up new avenues in theoretical and empirical research in this area.

We are particularly interested in micro- and meso-level studies of sociocentric or egocentric networks, and their association with migration contexts, environments, and outcomes. Topics of interest include, but are not limited to:

• The role of social networks in different migration phases (initiation, transit, settlement, etc.);
• The composition, structure, size, spatial dispersion, dynamics etc. of migrants’ personal or egocentric networks;
• Networks, social support and migrant health;
• Networks and ethnic identity, ethnic segregation, or ethnic neighborhoods;
• Social relationships and migrant transnationalism;
• Social networks in specific migrant populations (e.g. elderly migrants, international students, return migrants);
• Network change among migrants and over the migration trajectory;
• Comparative studies of networks and migration (e.g., migrants vs. non-migrants, different migrant generations, forced vs. voluntary, documented vs. undocumented, female vs. male migrants, etc.);
• Mixed-methods studies of migrants’ social networks.

Guy Harling, University College London (g.harling@ucl.ac.uk)

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. Finally, we would be delighted to include work evaluating how interventions change social support and thus health in a network context.

In previous iterations, 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.

This session will be populated from submissions to the open call for abstracts for EUSN 2022.

Stefano Ghinoi, University of Greenwich (s.ghinoi@greenwich.ac.uk)
Riccardo De Vita, University of Greenwich

In the last years, social network analysis (SNA) has been widely applied in business and economics studies, focusing on different levels of analysis and actors – small and medium enterprises, multinational companies, local and international institutions, and non-governmental organizations. One of the major focal points of the innovative efforts for such actors has been the definition, development, and implementation of sustainable practices, in order to change production paradigms and addressing emerging requests from local communities and policymakers, such as the achievement of the Sustainable Development Goals (SGDs) and the introduction of a circular economy system.

This session is looking for contributions that specifically concentrate on the application of network theories and methods for investigating the application of sustainable practices. We encourage scholars to submit proposals using both qualitative and quantitative approaches, and drawing on different datasets. Moreover, theoretical contributions and empirical analyses are all welcome, as well as case study papers representing all experiences that have emerged in different regions and countries. Possible topics for article submission include, but are not limited to:

• Inter- and intra-organizational networks and sustainable practices;
• Sustainability policies and networking;
• Sustainable Development Goals;
• Strategic partnerships for supporting sustainable business innovation;
• Circular economy and social network analysis;
• Sustainable practices at local level;
• Social relationships and social sustainability;
• Supply chain management, networks, and sustainability.

Riccardo De Vita, University of Greenwich
Yasaman Sarabi, Edinburgh Business School, Heriot-Watt University (y.sarabi@hw.ac.uk)
Matthew Smith, Edinburgh Napier University
Guido Conaldi, University of Greenwich

More and more institutions across the world now include teaching of Social Network Analysis (SNA) as part of their offer. SNA is taught across different levels and either as a separate subject, often presented as a methodology, or embedded within specific disciplinary contexts. In some cases, SNA is the object of full programmes of study. The emphasis of teaching also varies across institutions, with some modules focusing on the theoretical concepts behind SNA, and others emphasising the use of software to perform SNA. Finally, universities, when introducing SNA concepts and ideas, need to be mindful of the expectations of students and employers, who are often interested in networking and successful networking behaviour in the workplace. Despite the growing popularity of teaching SNA, the SNA community lacks a formal forum to exchange ideas and practices about teaching SNA. This session seeks contributions on teaching SNA, focusing on best practices, challenges, and pedogeological reflections. We aim to create a platform to exchange views about the opportunities and challenges in teaching SNA and establish a first opportunity for teachers of SNA to share their experiences.

We welcome submissions discussing any issue associated with the teaching of SNA, 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;
• Teaching SNA and networking behaviours;
• Experiments and SNA;
• Teaching SNA in different cultural contexts.

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.