Statistical Network Modelling
Tom Snijders, University of Groningen
and University of Oxford

Invited speakers:
Johan Koskinen, University of Manchester
Peng Wang, Swinburne University
of Technology in Melbourne

Traditional network metrics describe parameters of observed networks. Meanwhile, understanding of the processes that influenced the formation of observed network structure requires statistical models that represent distributions of networks with similar structural features as the observed network, hence inferring local network processes based on estimated parameter values. By considering the interdependent nature of network links and the properties of the involved nodes, current statistical modelling techniques allow to account for different network configurations, as well as for nodal and dyadic level attributes, in order to determine the sets of factors that have strong influence on the formation of an observed network. There are extensions for longitudinal data revealing how the interplay of those factors unfolds in time.

Moreover, the recent model developments for multi-partite networks comprised of links between ontologically different nodes, multiple networks consisting of multiple types of links among the same set of nodes, as well as multilevel networks combining multi-partite and unipartite networks, allows inferences on how these networks affect one another by simultaneously account for relations within and between networks of different kinds – inter-personal networks, semantic networks, organizational networks, material objects networks, networks of spaces, etc. For example, one can model how the usage of concepts connected in a semantic network is related to the existence of inter-personal ties. The models can also be compared to find differences and similarities in formation of networks in different cultures, societies, states, economies, organizations, cities, etc.

This session invites papers discussing methodological issues in statistical network modelling. Particularly encouraged are multi-partite, multilevel and multiple models and hypotheses driven by developments in multimode network theory and applications along with the existing hypotheses tested on new data.

Presentations of developments in relevant software would also be appreciated.

Socio-Semantic Networks
Iina Hellsten, University of Amsterdam

Invited speaker:
Camille Roth, Sciences Po, Paris

In recent years, research jointly considering semantic and social network data has expanded, and options to relate those have been explored theoretically and methodologically. Advanced analytical methods and the increasing availability of large data sets, in particular social media data, have been mutually reinforcing and catalyzing research into combining semantic and social networks. Prior work has shown that both the structure of social relationships and discourse/meaning sharing contribute to the emergence and spread of knowledge and culture. The innovation resides in the contribution that social network analysis offers for studying the relationships between social structures and the discursive/meaning structures that individuals or communities share.

One trend has been to consider similarities between people’s discourse as a specific form of social ties. The resulting socio-semantic network can then be combined and contrasted with other types of social networks based on friendships, advice, influence and other type of social relationships. Another trend is to jointly consider social actors, concepts and relations between them as forming multilevel networks. In both trends, discourse and social ties are expected to coevolve as actors share meanings or differ in those while their social ties transform.

In this emerging field, theoretical and methodological questions abound. For example: Which discourses and communities should be analyzed with regard to a particular research context and question(s)? How does the method chosen to assess similarities in discourses/meanings (topic/theme analysis, semantic fields, concepts and lines between them, exact words) impact the results? What are the ways to analyze the coevolution of social and semantic networks? To what extent can social network measures be applied to semantic and socio-semantic networks? How can statistics of those networks be compared? Which socio-semantic network configurations can be used in statistical models (e.g., ERGMs)? What kind of theorizing is triggered by research of socio-semantic networks?

Interested participants are invited to submit theoretical, methodological or empirical papers, contributing new perspectives on the questions how, when, and under what conditions social relationships, content and meaning structures can be connected via network research; or what approaches are suitable to strengthen the understanding of the connections between the structure of social relations and meaning.

Papers should fall into one or several of the following thematic areas:

- Theorizing about relationships between meaning structure, content structure and social structure

- Qualitative and quantitative methods to relate meaning structure and social structure

- Multilevel and multimode socio-semantic networks

- The relationship between semantic similarity and social ties

- Joint semantic network analysis of message content and social network analysis of information channels

- Applying social network analysis techniques to semantic and socio-semantic networks

- Using semantic network data to capture social structures between actors

- Semantic structuring throughout conversations in networks.

Network Analysis of Cultural and Social Duality
John Levi Martin,
University of Chicago

Invited speaker:
Sophie Mützel, University of Lucerne

In recent decades, the duality of culture and social structure as mutually constitutive has been in the focus of social science with a corresponding interest in symbols, meanings, texts, cultural frames, and cognitive schemas when studying social processes (Bourdieu 1984; Friedland and Alford 1991; Mohr 1998; Aleksander 2003). One stream of research applied network perspective to the level of institutions and/or fields, examining power control of social phenomena that involves cultural structures and social structures as conditioning symbolic ones (DiMaggio 1986; Mohr 1994; 2009). It has also been argued that the relations between the cultural and the social reveal themselves at the level of social (inter)action and practice, as individuals tend to switch between cultural classifications and social relations (White 1992), play on the gaps and contradictions in fields’ logics (Friedland and Alford 1991; Friedland and Roger 2009), and are guided by matters at hand (Bourdieu 1990) and by intersubjective relations (De Nooy 2003; Godart and White 2010). In those processes, meaning – which is then further integrated into cultural constructs and affects large-scale social structures - continuously emerges bottom-up.

Methodologically relevant are two-mode perspectives on meaning (Breiger 1974; 2000; Mohr 1994; 2000; Breiger and Mohr 2004) with their links to multimodal and multilevel data, such as in the socio-semantic approach (Roth 2013) and analytical techniques employing formal statistical modeling, including SAOMs and ERGMs. Another possibility is qualitative approaches - addressing the duality of structure and culture as meanings emerging from interaction, such as analysis of relational events (White 1992; Fuhse and Muetzel 2011) and sequences of events analysis (Bearman and Stovel 2000). There are also mixed methods using, for example, Galois lattices (Yeung 2005) or meaning contrasts analysis based on textual data.

The session welcomes papers applying these or other network analysis methods to study the duality of culture and social structures either on the micro or the macro level, particularly welcoming papers addressing relations between the two levels.

Qualitative Network Analysis
Robin Wagner-Pacifici, New School
for Social Research


Currently, more and more qualitative researchers join the field of social network analysis, while quantitative network scholars increasingly rely on qualitative approaches. Such a situation of cross-pollination can be particularly fruitful for the development of growing areas of network research, one of which is multimodal networks. This session is aimed to facilitate contributions that use qualitative frameworks. One important issue is collection and coding of data on interpersonal networks, semantic networks, cognitive networks, organizational networks, material objects networks, spaces and places networks, or other types of networks in diverse settings. Those settings may include a wide range of spheres, from science and technology or organizational and institutional contexts, to social movements, urban spaces, local communities, artistic groups, and others. The papers submitted to the session may discuss the potential in network data collection of ethnography-based methods and narrative inquiries, or combinations of those with more formal techniques such as network surveys or automated textual analysis. Other proposals are also most welcome. Especially interesting are techniques for longitudinal data collection and analysis.

Other pivotal issues are dealing with analytical techniques of qualitative network analysis that study how lines and nodes of ontologically different types are related – including multiple and multilevel perspectives – as well as strategies to compare networks across cultures, societies, states, economies, and cities. In this regard a possible question to address at the session is how network visualizations can be analyzed in a qualitative logic. Qualitative analysis techniques tackling the co-evolution of different types of networks are particularly welcome.

Theoretical grounding and methodology of qualitative network data collection and analysis techniques can also provide the focus of papers submitted to this session.

Finally, papers dealing with the ways to integrate software in qualitative network research would be of interest.

Socio-Material Network Analysis: Relating Social Structure, Practices and Physical Contexts
Nikita Basov, St. Petersburg State University

Social practices and encounters are always spatially patterned and subject to the powerful influence of the material contexts they are embedded in (Urry 1995). This involves multiple nonlinear effects as materiality both gives opportunities to, and puts constraints on, human activity. Things and physical spaces can constitute stimulating working environments, provide platforms for debates and cooperations, promote mutual learning of people, and provide cohesion of groups and organizations. At the same time, they can turn into objects of envy and competition and impact the (re)production of material and symbolic barriers between people and groups. Different objects are associated with different meanings, provoke various emotional responses and have different potential to generate motivation, trigger communication, and maintain identity and sociality. Network analysis can be useful to conceptualize how structures of physical contexts and social structures constitute each other. This session welcomes network-theoretical elaborations on the complex, dynamic processes in which human relations shape and are shaped by material contexts.

In the framework of the session we also propose to consider the methods of tracing cross-level links between individuals and material objects / spaces, as well as within-level relations between material objects and/or spaces themselves. One of the possible issues to discuss is the potential and limitations of sociological ethnography (e.g. qualitative observations and photo-elicitations) and interviews. Another issue is related to how qualitative methods can be effectively combined with quantitative ones, such as sociometric surveys. Finally, we suggest reflection on how the empirical data collected with mixed methods can be further subjected to formal analysis - jointly approaching material and social dimensions with such network analysis techniques as bipartite and multi-level network analysis, and open discussion of the methodological challenges in such complex research designs.

Networks in Art: Practice and Structure, Meanings and Interactions
Aleksandra Nenko, NRU ITMO
Margarita Kuleva, NRU Higher School of Economics

From a pragmatic point of view, art is a collective act opposed to individual practice. The social nature of art has been addressed from different standpoints: from revealing how new styles in art emerge due to changes in its institutional structure (White & White 1965), to showing power relations in the art field (Bourdieu 1983). Also, by defining the conventionally organized operations in the art world (Becker 1983) and arguing the importance of everyday interactions and friendly dynamics in creative collaborative circles (Farrell, 2003, Collins, 2015). Network analysis is a powerful tool to capture the multiplicity of these relations in art.

Network analysis has been extensively used to develop Bourdieu’s and Becker’s elaborations on the social structure of art: network effects of positions were found in the space of cultural production (Muntanyola & Lozares, 2006; Crossley 2009; Bottero and Crossley 2011); formation of evaluative categories and artistic judgements have been studied (de Nooy 2009); artistic careers have been taken as trajectories through professional institutions and events (Giuffre 1999, Moureau & Zenou, 2014); and creative performance has been shown as an effect of the small world structure (Uzzi & Spiro 2005). The session welcomes papers continuing the work from within these established frameworks.

Network analysis also allows to empirically locate and relate artistic practices and operationalize concepts of focused interaction (Goffman 1961), artful practices (Garfinkel 1967), and habitus (Bourdieu 1980; Wacquant 2015). Applied to textual data network analysis, it provides tools to study how meanings emerge from interactions between artists. Network analysis can be used to capture the material embeddedness of artistic practice in the immediate settings of studios (Farias & Wilkie 2016), local buzz (Currid & Williams 2009) and networked complexity of a ‘creative’ city (Comunian 2011). Network analysis can also capture the positions of artworks in structures of relations between actors, while the former are collaboratively created through embodied and materially embedded communication (Albertsen & Diken 2004). Studying the composition of art networks in connection to public participation reveals possibilities for social empowerment through art, and shows ways to implement principles of relational aesthetics (Bourriaud 1998). We welcome papers that adopt network analysis to study the variety of phenomena in art including those proposing alternative perspectives.

This is a thematic session, so the methodological options are multiple. Particularly encouraged are papers on methodology and applications of multimodal network analysis, including those studying the duality - for example, of places / events and artists, social and cultural structures, actors and objects - in artistic settings. This session will put together papers that are empirically sound with the detailed interactions that make the rehearsal a material context for action. We also expect papers on both micro and macro scale studies of social relations between individuals, institutions or meanings.

Making Sense of Big Network Data: Testing Hypotheses on New Data
Camille Roth, Sciences Po, Paris

Traditionally, network data have been difficult to collect. Observation of network ties among people is time-consuming and therefore restricted to ties within small groups. There are limits to the number of network contacts a respondent is able and willing to list in a questionnaire (Bernard et al. 1990) and surveying the ties of and among network contacts requires snowballing samples that increase quickly in size (Laumann, Marsden & Prensky 1983). It has long been recognized that networks can be constructed from archival records (Burt & Lin 1977, Burt 1983), but the advent of large-scale digital data storage is now offering access to network data that are nearly as limitless as social networks themselves. The Internet, as a network of pages linked by hyperlinks, logs of contacts between persons through (mobile) phones, social networking sites, and so on, links between people and products from purchases with credit cards or customer cards, geographical proximity between persons based on GPS tracking; relational data suddenly seem to be generated everywhere.

The sheer size of the data poses technical problems, however, these are not central to the session. Instead, we invite contributors to focus on the substantive questions that can be answered with these types of data and the methods needed to find answers. We welcome proposals and examples of ways in which (long-)standing hypotheses from the social and behavioral sciences may be put to new and perhaps better tests using Big Network Data. For example, availability of data on the overall structure of the Internet allowed a new test (Barabási & Réka 1999) of the Matthew Effect (Merton 1968) or Cumulative Advantage Processes (De Solla Price 1976), which is now commonly known as Preferential Attachment. In addition to analyzing the overall structure of a network, large-scale network data may also serve as a sampling frame for clever selection of ego-networks or pairs allowing tests of network hypotheses such as a tendency for transitive closure of social contacts (Kossinets & Watts 2006). Novel approaches to theoretically driven network questions are likely to emerge, and we welcome papers introducing them in traditional fields, as well as emerging research topics such as innovation ecosystems, intellectual landscapes, and network cultures, to name a few.

Social Media Networks
Svetlana Bodrunova, St. Petersburg State University

The rise of social media provides large scale data on social and semantic network in online discussions. Social media has been considered as a virtual space for social interactions, but specific social media also has its particular technical functions that may facilitate or block certain types of uses of the ‘space’. We approach the concept of social space as a metaphor for a new type of place for social interactions, the main characteristics being the flexibility of boundaries between social groups with unclear group membership. This poses challenges for research into the social and semantic networks in the various types of social media, such as online communities, blogs, Facebook, YouTube, Twitter and other social media forums that are also linked to each other. This new social media data enables more varied approaches that combine social, content and meanings networks online.

The rise of social media has also lead to more and more data being collected about us and our activities. Our social media interactions and our online search and shopping behaviour, but also offline location tracking and sensor and surveillance networks are all generating large, often real-time data sets. Potentially, these could help answer important questions facing society today. But processing them productively represents a real challenge, at the interface of social and computer science. Meeting that challenge requires not only thorough comprehension of the methodologies involved in analysing social media data, but also a theoretical understanding of interlinked social media data, and the potential legal and ethical factors. The session on social media networks focuses on the theoretical and methodological challenges posed by social media interactions.

In particular, we invite presentations that combine social network measures with semantic networks, and focus on multi-mode networks of actors and the content of their communications.

Networked City: The Multiplicity of Urban Links and Nodes
Aleksandra Nenko, NRU ITMO

Invited speaker:
Christof Parnreiter, University of Hamburg

Since Lefebvre 2003 [1970] announced ‘planetary’ urbanization, researchers have been calling for new paradigms in theory and methodology to grasp the city's complexity. However, the apt remark by Soja (2000: xii) remains true ‘it may indeed be both the best of times and the worst of times to be studying cities’ because of the ‘restless periodicity and extraordinary slipperiness of the urban phenomenon itself’ (Brenner et al. 2011 : 226). The concept of ‘networks’ has become a new metaphor to thinking the city complexity, and is elaborated in the framework of two influential conglomerates of research. First is represented by works of M. Batty (2005; 2013) who considers urban dynamics in the context of complexity theory and models myriads of processes and elements that combine into organic wholes. Elaborating urban morphology and patternology, Batty shows different kinds of networks as structural under-layers of multiscale urban dynamics.

Second is assemblage theory and actor-network theory which incline thorough investigation of sociomaterial configurations and non-human agencies in cities. Applications of this approach in urban research were presented by Farías and Bender’s volume (2010). Following this strand of thinking McFarlane (2011) describes the city through ‘grammars of gathering, networking and composition’ of different agents (p. 207). The assemblage approach to cities is criticized for lack of analytical and critical power by Brenner et al. (2011) however is advocated further by Farias (2011).

Parallel and in connection to these two meta-narratives, there are multiple applications and achievements of network analysis in considerations of the city, summed up, for example, by Neal (2013) who defines three levels of network phenomena: networks of urban communities, the city as network and networks of cities.

Network analysis allows researchers to explain the relations between diverse networks in the urban environment - from interpersonal to technical ones - influencing each other. There are numerous examples of such relations and influences between urban networks. To name a few, those are segregation and cohesion in urban communities as a consequence of spatial structure of the city streets and meeting spots, alternative centers of urban life based on clustering of urban practices represented in social media, e-neighborhoods and virtual spatial communities formed via Internet, paths and landmarks determining perception of city environment with its flows and the dynamics of city life.

We invite both papers that present comprehensive elaboration of theoretical assumptions and pick up networks as ontologies and those using network analysis methodologies to address the complexity of urban phenomena in European urban landscapes and beyond.

Social Movements and Collective Action as Network Phenomena

The role of social networks in collective action processes has been analyzed in the last few decades from a plurality of perspectives. A substantive bulk of research has been devoted to the mechanisms behind individual decisions to become – and remain – committed to the pursuit of collective goods. Whether the focus was on employees organizing to demand better working conditions, residents joining together to clean their neighborhood streets, or radical activists committing to a long-term project of social transformation, how embeddedness in networks affects people’s decisions to engage in collective action has attracted considerable attention (Diani 2004). At the same time, research has also mapped the structure of the inter-organizational exchanges that develop between groups and organizations interested in similar issues, whether in the form of ad hoc coalitions or fully-fledged social movements (Diani and Bison 2004).

Although most network research on collective action has been conducted by social movement scholars (Diani and McAdam 2003), the two dimensions do not necessarily overlap, from theoretical and methodological perspectives. This session invites submissions from scholars interested in collective action at large, i.e., in the joint pursuit of collective goals by individuals and/or organizations, whether of the radical or the moderate type, and regardless of whether the focus is on protest activity or service delivery as in the case of volunteering (Wilson 2000). Submissions focusing on quantitative or qualitative approaches to social network analysis are both welcome. So are studies of ego-networks as well as explorations of complete networks. We also encourage proposals from scholars investigating collective action through virtual online connections, such as social networking sites (Ackland and O’Neil 2011; Gonzalez-Bailon 2009), the spatial dimension of social networks (Nicholls, Miller, and Beaumont 2013), and the time evolution of collective action networks (Mische 2008).

Network Analysis of Political and Policy-Making Domains
Artem Antoniuk, St. Petersburg State University

Invited speaker:
Nina Kolleck, Freie Universität Berlin

The study of policy and political networks has a distinguished history in the social sciences. David Knoke (1990) identified the theoretical objectives of the field as ranging from explaining and predicting collective policy decisions and outcomes, to exploring how networks form, persist, and change over time. The study of political networks also engages with theories of political influence, aiming to explain how relations among actors can affect their political identity and behavior. The thematic scope of the session includes studies of policy-making and political processes through the network perspective, focusing on relational structures and interactions between governmental and nongovernmental organizations, interest groups, and individuals. From a methodological perspective, such research requires the collection of attribute data about actors, and of relational data determining the ties between them. It is also important to have institutional and social data to contextualize the political framework within which political decisions are made.

The session welcomes papers focusing on, but not limited to, the following aspects of political and policy networks:relations between actors shaping their political attitudes, preferences, and opinions; implications of network structures for actors engaged in contesting and collaborating within specific public policy arenas; cross-country similarities and/or differences in the structure of policy networks; policy network change across different stages of the policy cycle; key players within policy space and privileged network positions, such as brokerage and centrality, reflecting actor political power.

There is a range of open questions emerging from active – and thus to an extent asynchronous – development of theory and methodology of political networks analysis, which paper authors are particularly welcome to address within this session. One of them concerns the evaluation of political weight and power of structurally central actors and groups in the network. This objective related to power and influence theories requires further development of the methodological network tools. Do the combination of network data and survey data, or rankings of influential actors made by magazines, provide sufficient attribute data for modeling power distribution in the network? Is it possible to test hypotheses about the interdependence between the relational structure as a variable that determines, or is affected by, the individual characteristics of specific political actors?

Particularly welcome are applications addressing topical issues of European societies.

Negative Ties and Signed Networks
Filip Agneessens, University of Surrey, Guildford
Patrick Doreian, University of Ljubljana
and University of Pittsburgh
Alexandra Gerbasi, University of Surrey
Nicholas Harrigan, Singapore Management University
Giuseppe (Joe) Labianca, University of Kentucky
Joshua Marineau, North Dakota State University
Károly Takács, MTA TK “Lendület” Research Center
for Educational and Network Studies (RECENS), Budapest

Researchers are now increasingly aware of the co-existence of positive and negative ties in networks and the need to study them together so as to get a more accurate portrait of the networks' contents and dynamics, as evidenced by an upcoming special issue on the topic at the journal Social Networks. In line with the conference overall theme, we invite abstracts for presentations on all aspects of studying signed networks, including theory, methods, and applications. We encourage a wide range of submissions both at the societal and at the level of individuals. Example works include (but are not limited to): the study of international conflicts and alliances; how subgroup faultlines affect intra- and inter-group conflict; understanding how threats within a network create needs for allies, and the implications for nodal power; how segregation and group formation could be understood in terms of positive and negative ties; methods and measures pertaining to negative ties and signed graphs; examining where bullying emerges in different segments of the society; and how the perception of negative ties poses unique challenges.

Mixed Methods in Network Analysis
Daria Maltseva, Anna Shirokanova and
Stanislav Moiseev, NRU Higher School of Economics

Social network analysis has institutionalized and become widely known as a form of quantitative methodology that uses various formal statistical and graph metrics to calculate the relationships between different actors (people, their groups, organizations, etc.) which are represented as networks. At the same time, in social network analysis there is a tradition of qualitative approach. Originally created in 1950s by social anthropologists, it developed in the late 1980s-90s, together with the stream of ‘cultural turn’ in sociology and the appearance of the field called ‘relational sociology’.

The next possible direction of the social network analysis development is the combination of quantitative and qualitative approaches which corresponds to the ‘mixed-methods strategy’ in social research. The main idea of this integration is to consider the ‘dual nature of social reality’ by focusing both on external network structures of relations and on the internal meanings of these relations.

This session welcomes papers discussing different issues on the integration of quantitative and qualitative approaches in network analysis, such as mixed methods research designs, techniques for data collection and extraction, software development, methodological approaches to interpretation, applied analyses of mixed data, and their theoretical foundation.

New Perspectives on Science and Technology Networks
Joshua Eykens, University of Antwerp

Social networks have always been (and will always be) fundamental for our understanding of human interaction, and as a result they have been studied within disciplines like the Sociology of Science (SS) and Science and Technology Studies (S&TS) for quite a while. Canonical work in this tradition has tended to map the dynamics of science and technology networks through various ways (cf. Callon, Law, and Rip, eds., 1986). These studies mostly make use of some peculiar and inventive methods derived from social network analysis techniques; the pinpointing of industrial invention (by mapping patent-networks), the analysis of scientific communication (by mapping citation networks), the analysis of semantic networks, etc. The digitalization of the scientific enterprise has brought about an enormous growth in the available data, and challenges us in various ways to come up with innovative new methods to encounter the new possibilities. It is continuously being shown that different Social Network Analysis methods are extremely useful in this light, but require considerable adjustments.

The fact that you are reading this call on your screen right now is a direct consequence of another recent revolution in science and technology; the social networking revolution. This trend becomes very tangible within science and technology communities when we think of online platforms like ResearchGate and But what are the immediate consequences of such social networking opportunities? Digital trends are changing the structure and dynamics of social networks in science, and we have the tools for studying and explaining these changes. Examples of questions which researchers are asking themselves today include; “What kind of change do they bring about in terms of scientific collaboration or even the publication visibility?”, “In which ways do they influence the applicability of classic bibliometric indicators?”, and “In which ways do they allow for so called altmetrics?”. Only recently academic interest has been shifting its attention to these issues.

We which to enhance these previously mentioned undertakings and encourage submissions of original social network research exploring the different structural and social dimensions of science and technology, both from a local and global perspective. The proposed research could be of theoretical, methodological or empirical nature. Presentations and papers are invited on topics and questions that might include, but are not limited to:

- Bibliometric methods informed by Social Network Analysis

- Citation networks (papers, journals, etc.)

- Social studies of science

- (Trans)national scientific collaboration networks

- The impact of new ICT’s on scientific networks

- Analysis of the use of informal social networks by scientists and for scientific purposes (i.e. ResearchGate, Academia, Facebook groups, etc.)

- Empirical studies of science making use of Social Network Analysis (i.e. innovation networks)

- The emergence and evolution of socio-cognitive structures in science

- Network theoretical excursions in the Sociology of Science and Science and Technology Studies.

Networks in Educational Environment
Daniel Alexandrov, Valeria Ivaniushina, Vera Titkova, Daria Khodorenko,
NRU Higher School of Economics - St. Petersburg

Educational researches focused on peer effects in various aspects of children and adolescents development. Studies look at both positive and negative effects of peer influence. In school context positive and negative outcomes are strongly related to different types of peer relations. The relationship between peer ties and their behavior could be determined by diverse factors - socio-demographic characteristics (age, ethnic status and others), class and school environment (class norms, school type), cultural norms of the country or region and so on.

Network analysis gives good impetus to studies of complicated relations between peer network and different types of behaviors and attitudes in the school/class environment. For example, to date there are ca. 5,000 articles about network and risk behavior among adolescents (Web of Science search results). Such diversity of studies requires a separate platform which aims at discussing the findings, research difficulties, and opportunities. International network conferences - Sunbelt & EUSN conference - organize sessions to discuss issues of adolescent behavior, positive and negative networks and peer influence.

In our session we are interested in network studies on different behaviors (attitudes) that can be related with well-being of adolescents and children at school: educational involvement, academic achievement, learning self-esteem, risk behavior, dropping out, extracurricular activities, health-saving, pro/antisocial behaviors, including SNA applications to online and blended learning and networks derived from interaction in LMS.

We welcome application of network analysis to diverse research issues and tasks, for example:

- detecting students’ behavior spreading;

- studying structure of social relations in different types of students’ behavior;

- studying the consequences of peer influence on the well-being of students in school;

- studying preventive measures which aim at reducing the involvement in some kind of risk behavior through working with peer networks;

- detecting moderating factors of relationship between students’ behavior and peer networks such as school / class climate, parental control, cultural norms and values;

- applications of social network analysis to online and blended learning;

- event models in xMOOCs;

- online social networks of students.

Shaping Social Media Discourse: The Roles of People, Institutions, Algorithms, and Other Network Agents
Svetlana Bodrunova, St. Petersburg State University

In the rising climate of post-truth and polarization of public discourses, there is, arguably, more and more attempts to curate information flows and create calculated publics (Bruns&Burgess 2011) instead of spontaneously emerging ad hoc issue publics (Habermas 2006; Bruns 2011) in online communication. On the other hand, the number of network agents (Latour 2005) both grows in number and diversifies by type, and today not only ‘ordinary users’ and institutional accounts play new roles in network constitution. There are also the so-called algorithmic gatekeepers (Napoli 2015) – the SNS platforms, search engines, news aggregators, automated news production machines etc. – who reshape the communication flows and provide new rules of the communication game. Altogether, this may result into networked gatekeeping (Meraz&Papacharizzi 2013) where new patterns of dominance and oppression of may arise within curated and one-sided discourses; or, otherwise, new patterns of empowerment via discursive citizenship may emerge across countries.

This session focuses on the role of organized grassroots actors, institutional accounts, platform algorithms, and inherent discussion structures in the formation of today’s discourses in social media. What are the relations between structural position and discursive strategies of the discussion participants? Do efforts to shape the discourse really work? What roles media and institutions play in the formation of structure and substance of social discussions? How do algorithmic ‘rules of the game’ impact our network neighbors? Does social representation, or activity, or connectivity, or status (as measured by network structure paramenters) matter for the discourse emerging in social media, and how exactly? Are left/right and other political divisions network-dependent? These and similar questions need to be addressed, and we welcome papers dealing with them, especially in comparative perspective.

Networks of International Organizations and Associations
Martin Koch, Bielefeld University
Alexander Kuteynikov, St Petersburg State University

Almost 40 years ago Harold Jacobson published his famous “Networks of interdependence: international organizations and the global political system” (New York: Knopf, 1979). Since then, international institutions as well as methods of analysis of networks have changed significantly. The number of intergovernmental structures have exceeded 7000, and the number of non-governmental organizations reaches 30 000 or even 50 000.

The topicality of studying networks with regard to International Organizations and Associations (IOAs) is required of the following. First, over the past few decades IOAs have moved from bodies with auxiliary or administrative functions to independent actors in all major areas of political/economical/social activities. They also entered in everyday life and interactions of people, organizations, enterprises, public institutions. Second, they have influenced new forms of relations, they become the cores of the networks themselves, they are centered on different political, economic and other activities, communications and relationships of international and domestic actors. Third, they activated inter-personal relations in a world scale. Not only limited numbers of closed group of people from elites, international functionaries, diplomates, epistemic communities are involved in international communications and activities. Currently, many social strata are internationalized and globalized.

An academic discussion of questions, submitted for session, will allow us to approach to update our fast ageing knowledge about international institutions, to find out methodological approaches on the study of IOAs, and to outline relevant theoretical models.

We are expecting for presentations/papers on:

- different types of networks of/in International Organizations and Associations (including State and non-state institutions);

- current state and prospective of networks approach to studies of International Organizations and Associations (IOAs);

- patterns and mechanisms of inter-state, inter-personal and state-personal relations/interactions in/around IOAs;

- international functionaries, including international civil service, others social/political groups, lobbyists, global groups, which is often identified as a world or global society, involved into IOAs;

- networks analyses, networks monitoring, big data analyses, case-studies related to IOAs;

- initiative subjects.

Networks of the Asia-Pacific Region
Alina V. Vladimirova, Institute of Oriental Studies
of the Russian Academy of Sciences

This session is co-organized in collaboration with the Center for Southeast Asia, Australia, and Oceania at the Institute of Oriental Studies RAS to discuss applications of network analysis in Asia-Pacific area studies. We would like to encourage papers that present a network approach to issues associated with the role of the region in the international system: analysis of relations within this most diverse group of states and societies in the world, analysis of countries roles as economic and military powers and, finally, analysis of actors and factors influencing global economic growth dynamics. We also welcome contributions that share a commitment to the rigorous network analysis of volatile international conflicts and focus on such cases as territorial disputes in the South China Sea. We especially invite scholars that deal with the evolution of international cooperation in the Asia-Pacific region, that model and compare its bilateral and multilateral types.

Social Networks as Valuation Devices: Reputation, Ranking, Recommendations
Margarita Kuleva, Alena Suvorova,
Daria Maglevanaya, Anastasiya Kuznetsova
and Ilya Musabirov,
NRU Higher School of Economics - St. Petersburg

The evaluation of the brands, products, venues and other people is heavily based on the other people’s opinion. Product reviews, web sites for tourists, dating markets, recommender systems, professional communities, forums, blogs and news affect our opinion and influence our choice. Social media become an easy and scalable instrument for sharing experience, showing impressions and expressing emotions. Valuating becomes an appropriate process for goods and services exploration due to their specific characteristics (Karpik, 2010). Moreover, instead of real pricing schemes, rankings and other assessment methods valuation could be implemented through relationships between agents in the network based on identifying their strategies in creating ties for different purposes (ex. disruption, conflict, dissent and controversy) (Helgesson, 2017).

The aim of the session is to bring together interdisciplinary scholars to examine the systems, devices, instruments and infrastructures that underpin various kinds of valuation (rating, pricing, ranking, accounting, funding, and assessing).

Network researchers of different areas as consumption, reputation, brand popularity, recommendations are cordially welcome to join this session.

Software workshops

Analysing Network Dynamics and Peer Influence Processes with RSiena
Tom A.B. Snijders, University of Groningen
and University of Oxford

This workshop gives an introduction to the statistical modelling of longitudinal social network data by means of stochastic actor-based models, implemented in the RSiena program (Snijders, 2017; Ripley et al., 2017). Longitudinal social network data are understood here as two or more repeated observations of a directed graph on a given node set (usually between 30 and a few hundred nodes), with or without associated observations of nodal variables.

Network Dynamics

Stochastic actor-based models for network evolution (Snijders, van de Bunt & Steglich, 2010) allow analysing global network change as emerging from local decisions, taken by the actors in response to their personal network environment. The definition of the model, model specification, and parameter estimation will be considered.

Peer Influence Processes

The next main topic is the analysis of network influence processes, like contagion or diffusion, taking place in dynamically changing, sociocentric networks (Steglich, Snijders & Pearson, 2010). Participants are introduced to the problems related to the identification of network influence, and to the stochastic actor-based approach for addressing these.

R implementation
Examples will be given of how these models are implementated in the RSiena package, part of the R statistical programming environment.


Workshop participants should have a basic understanding of model-based statistical inference (including, say, logistic regression), some prior knowledge of social networks. Participants who bring their own laptop to the course (Windows, Mac or Linux), with the R statistical software environment and a recent version of the RSiena package pre-installed, will be able to follow the examples of the RSiena implementation hand-on. RSiena can be installed as
install.packages("RSiena", repos="")
or downloaded from


Ripley, Ruth M., Tom A.B. Snijders, Zsofia Boda, András Vörös, and Paulina Preciado (2017). Manual for RSiena. URL:

Snijders , Tom A.B. (2017). Stochastic Actor-Oriented Models for Network Dynamics.
Annual Review of Statistics and Its Application, 4, 343-363.

Snijders, Tom A.B., Gerhard G. van de Bunt, and Christian E.G. Steglich (2010). Introduction to stochastic actor-based models for network dynamics. Social Networks 32, 44-60.

Steglich, Christian E.G., Tom A.B. Snijders, and Mike Pearson (2010). Dynamic Networks and Behavior: Separating Selection from Influence. Sociological Methodology 40, 329-393.

SIENA website:

Multilevel ERGM Analysis with MPNet
Peng Wang, Swinburne University of Technology in Melbourne

In this hands-on workshop, participants will learn the fundamentals of estimating Exponential Random Graph Models (ERGMs) with MPNet – a software developed to investigate the structural features of networks. The workshop will start with a brief introduction to the overall logic of estimating (single-level) ERGMs before introducing the recently developed multilevel ERGMs. The latter class of models enables researchers to investigate the influence of structure at one level of analysis on structure at a different level, while taking into account the complex interdependencies that exist within and between levels. For instance, interpersonal networks between managers at the micro-level might interact with alliance networks of the organizations they are nested in.

The workshop will start with a brief introduction to the overall logic of estimating (single-level) ERGMs before introducing the recently developed multilevel ERGMs. The latter class of models enables researchers to investigate the influence of structure at one level of analysis on structure at a different level, while taking into account the complex interdependencies that exist within and between levels. For instance, interpersonal networks between managers at the micro-level might interact with alliance networks of the organizations they are nested in.

Throughout the workshop, participants will work through short exercises to get familiar with the graphical user interface and output of the MPNet software. Moreover, we will discuss various case-study examples that will provide the participants with a good understanding of the possibilities that multilevel ERGMs offer for social scientists.

Requirements: Some basic familiarity with social network analysis will be helpful. Participants are required to bring their own laptops with MPNet installed. Note that MPNet is not compatible with Mac OS without a compatible Windows parallel.

MPNet program and manual:

Bayesian Analysis of Networks Using ERGM
Johan Koskinen, University of Manchester

This workshop will provide an introduction to ERGM and how to estimate and fit an ERGM using a Bayesian perspective. A Bayesian inference procedure offer a little more flexibility than the standard maximum likelihood but more importantly, the inference for uncertainty about parameters is richer. In addition to working through simple examples we will also explore various more advanced issues. We will fit models to data that has been collected though snowball sampling as well as analysing different model specifications for data where we have non-respondents. We will also touch briefly on analysing multiply observed networks, say, friendship networks collected for multiple different school classes.

Experience of network analysis is assumed but no prior experience of using ERGM is necessary. Working knowledge of standard statistical tools is a prerequisite for benefitting fully from the workshop but knowledge of Bayesian inference is not necessary. All hands-on work will be carried out in the program R and it might be helpful to have some prior exposure to R (links to online training resources will be posted closer to the date).

Estimating Dynamic Network Actor Models (DyNAMs) with the Goldfish Software
James Hollway, Graduate Institute Geneva

The advent of electronic communication, social media, and human sensor technologies and the digitalisation of many archives has generated a wealth of temporally specific relational data for social scientists to explore. Ties come with details about when they begin and, sometimes, end, giving us information about the order and duration of ties. This workshop introduces and compares different approaches for the analysis of time-stamped network data with special attention to the dynamic network actor class of longitudinal statistical network models (DyNAMs). The goal is to provide an overview of research problems that relate to time-stamped network data, to enable participants to conduct basic analyses with the Goldfish package in R, and to introduce conceptual and practical differences between models that have been proposed, in particular, focusing on differences between actor-oriented and tie-oriented approaches.

The practical elements of the workshop (about 50%) introduce Goldfish, a new R package for the analysis of time-stamped network data. In particular, three types of models are introduced, compared, and practically applied.

1) Actor-oriented models for undirected coordination ties. Typical examples are research problems found in the political sciences (e.g., the creation and dissolution of international treaties) and economics (e.g., coordination between financial institutions) and are concerned with the creation of undirected, bilateral agreements that are the result of a coordination process.

2) Actor-oriented models for directed events. Typical examples are sequences of interaction events (e.g., phone calls) or directed transactions (e.g., financial transactions).

3) Both actor-oriented models are compared to the tie-oriented relational event model which can also be estimated with the Goldfish package.

The practical elements make use of R scripts that are distributed to participants in advance. Participants can further bring their own research problems and their own data. Based on the number of participants, a limited amount of time will be reserved to discuss these.

Prerequisites: Basic understanding of R. Basic understanding of SIENA or other statistical network models is helpful.

Equipment required: A projector, wifi access, power sockets for all participants, possibly also a Mac lightning adapter to VGA or HDMI or whatever is required by the projector

Material given: Will be published online.


Butts, C. T. A relational event framework for social action Sociological Methodology, 2008, 38, 155-200

Stadtfeld, Christoph, James Hollway, and Per Block. 2017. “Dynamic Network Actor Models: Investigating Coordination Ties Through Time.” Sociological Methodology 47: 1–40.

Stadtfeld, Christoph, and Per Block. 2017. “Interactions, Actors, and Time: Dynamic Network Actor Models for Relational Events.” Sociological Science 4: 318–52.

Stadtfeld, Christoph, James Hollway, and Per Block. 2017. “DyNAMs and the Grounds for Actor-Oriented Network Event Models: a Response to Snijders and Butts.” Sociological Methodology, 56–67.

Network Visualization Tools
Camille Roth, Sciences Po, Paris

This workshop aims at presenting and illustrating the wide variety of visualization platforms which rely on a network ontology -- be it about social networks, semantic networks, or both. To this end, beyond focusing on a series of tools and integrated data processing platforms, this session will adopt a comparative approach to identify and discuss the prospects, features and possible limitations of available tools.

The goal is to equip participants with a critical feeling of the underlying assumptions made by a particular tool, in order to knowingly decide which one to use in which context (both from an epistemological and empirical viewpoint).

In particular, we will discuss two main types of tools:

- All-Purpose Tools.

On the side of social networks, we will cover classical and widely-used tools such as GePhi (its well-known large graph visualization abilities) and Pajek (whose use in social network analysis appears to be widespread). On the side of text mining, we would address low-level tools such as "NLTK" or "treetagger" and shed some light on the corresponding Natural Language Processing (NLP) assumptions and methods.

- Specialized Platforms.

We will present a diverse selection of integrated platforms whose task is to take care of most of the data processing workflow, from pre-treatment to visualization. Often, such platforms provide dashboards to examine arrays of datasets by implementing and applying a given network-analytic theory (e.g., following a specific set of hypotheses on what a cluster is, how their evolution can be measured). Here, beyond the aim of getting acquainted with these tools, we will emphasize the underlying theories and parameterizations which each platform follows -- illustrating further this point by applying (when possible) distinct platforms on identical datasets.

Analysis of Bibliographic Networks
Vladimir Batagelj, IMFM Ljubljana and AMI UP Koper
Daria Maltseva, International laboratory for
Applied Network Research, Moscow


Bibliographic networks consider different types of relations between publications and their authors, thus underlying different patterns of collaboration in science (co-authorship, co-citation, citing). Data for such networks can be quite easily obtained from special bibliographies (BibTEX) and bibliographic services (Web of Science, Scopus, SICRIS, CiteSeer, Zentralblatt MATH, Google Scholar, DBLP Bibliography, US patent office, IMDb, and others). Besides names of authors and titles of their works, more detailed information about them can be obtained: institution, country, time of the first work, time of the last work – for authors; publisher, journal, editor/s, number, volume, pages, key words, time of submission, language, classification/s – for works. With different procedures of networks transformation we can get many different kinds of mostly two-mode networks and study relations between different entities included in data bases (works, authors, journals, key words, institutions, countries, etc.).

However, producing the networks some problems can occur, connected to the synonymy and homonymy, lack of standardization of names and key words, errors, etc. For Russian language, an extra problem is that many tools for network production and analysis works well for the Latin alphabet, while they are not adapted for Cyrillic. Another problem is that networks obtained from the bibliographic data bases can be large (hundreds of thousands of nodes), and their analysis can be quite time and computational consuming. The data cleaning can take most of the available time.

Beside the basic networks extracted from bibliographic data we can produce additional networks using network multiplication. In this transformation a proper normalization of networks is crucial. In analysis of bibliographic networks we can consider also the time (publication year).

Dealing with bibliographic networks we use a special program for analysis and visualization of large networks called Pajek (, free for non-commercial use), which is being developed by Vladimir Batagelj and Andrej Mrvar (University of Ljubljana) from 1996, as well as some special programs in Python and R, that provide all necessary procedures to make bibliographic data ready for the analysis.

During our workshop we would like to present the network approach to bibliographic data and different methods used for their analysis, covering the questions of getting the data and preparing it, as well as to discuss some problems occurring when dealing with data in Russian language (based on the on-going analysis of Russian scientists working in some sub-fields). Among other, we will present a measure of collaborativness of authors with respect to a given bibliography and show how to compute the network of citations between authors and identify citation communities. The participants of the workshop will learn how to collect some bibliographic data, transform them into networks, and apply the discussed techniques of network analysis to them, using Pajek.

Requirements for the participants: basic knowledge of network analysis is needed.

Technical requirements: computer; links to programs to be installed will be sent to all the registered participants before the event.

Round tables

Networks of States and Persons in International Institutions
Aleksandra Kaasch, Bielefeld University and
Anatoliy Boyashov, Bielefeld University

Anatoliy Boyashov, Bielefeld University
Alexandra Kaasch, Bielefeld University,
Martin Koch, Bielefeld University,
Alexander Kuteynikov, Faculty of Sociology,
St Petersburg State University,
Elena Moskalchuk, Faculty of Sociology,
St Petersburg State University

There are two levels within international institutions: the inter-state and the inter-personal. Whereas the inter-state level is usually a formal-structural level of cooperation among states, the inter-personal level addresses the working level within international institutions where different individuals – be they states representatives, delegates or officers in the administration – interact. We are interested to discuss how both levels are interrelated or even interacting and thereby shaping the character of PFICs. What is the nature of these relations? What are the specific functions of both levels? In which cases and under what conditions is the inter-state level dominant and or the inter-personal?