Programme

7.07.2020

09:00

Registration of the workshops' participants and morning coffee

 

10:00

WORKSHOPS

 

12:00

COFFEE BREAK

 

12:30

WORKSHOPS

 

14:30

LUNCH FOR WORKSHOP PARTICIPANTS

 

15:00

REGISTRATION AND WELCOMING COFFEE

 

15:30

CONFERENCE OFFICIAL OPENING. KEYNOTE TALK

 

16:30

COFFEE BREAK

 

17:00

PARALLEL SESSIONS

 

8.07.2020

09:00

REGISTRATION AND MORNING COFFEE

 

10:00

PARALLEL SESSIONS

 

12:00

COFFEE BREAK

 

12:30

PARALLEL SESSIONS

 

14:30

LUNCH

 

15:30

KEYNOTE TALK

 

16:30

COFFEE BREAK

 

17:00

PARALLEL SESSIONS

 

19:00

BREAK

 

20:00

CONFERENCE RECEPTION

 

9.07.2020

09:00

REGISTRATION AND MORNING COFFEE

 

10:00

PARALLEL SESSIONS

 

12:00

COFFEE BREAK

 

12:30

PARALLEL SESSIONS

 

14:30

LUNCH

 

15:30

KEYNOTE TALK. CONFERENCE OFFICIAL CLOSING

 

16:30

BREAK

 

17:00

CULTURAL PROGRAMME

 

Sessions

Networks and Culture
Chair:
Frederic Godart, INSEAD

Invited speaker:
Jan Fuhse, Humboldt University Berlin
 

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 - that further gets 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 (Basov, de Nooy, and Nenko, 2019).

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

Semantic and Socio-Semantic Networks
Chair:
Iina Hellsten, University of Amsterdam

Invited speaker:
Camille Roth, Humboldt University Berlin
 

This session is dedicated to research applying network analysis techniques to texts. We are also interested in work combining text networks with social network data - in order to expand our understanding of the meaning both of texts and of social relations.

On the one hand, we are looking for contributions that bridge the gap between theories related to language use, and/or networks and methods/tools for utilizing text data for network analysis. We are particularly interested in work that advances theories about the use or production of language or text data and integrates with network-analytical methods and techniques. More specifically, what are the main types of relations between words and the means to measure them? Which network metrics should apply to the networks of such relations? Do such metrics of social networks as centrality, density, or clustering apply to networks in which the nodes are topics or terms and relations are thematic associations or similarities? Should we look for alternative metrics and what might these be? We particularly encourage contributions reflecting on these issues and empirically investigating them.

On the other hand, the recent years witnessed expansion of the research jointly considering semantic and social network data. 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.

We invite papers on, but not limited to, the following topics:

- Theorizing about meaning structure, semantic structure and social structure, and the relations between them;

- Qualitative and quantitative methods to study semantic structure, including in relation to social structure;

- Multilevel and multimode semantic and socio-semantic networks;

- Semantic similarity and its relation with 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;

- Usage of semantic network data to capture social structures between actors;

- Semantic structuring throughout conversations in networks.

Finally, we invite applications of semantic and socio-semantic network analyses in various fields.

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

Invited speaker:
Frederic Godart, INSEAD
 

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 and puts constraints to 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 object 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 individuals shape and are shaped by material contexts.

In the framework of the session we also propose to consider the methods of tracing relations between objects/spaces and/or between individuals and material objects/spaces. 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 to reflect on how the empirical data collected with mixed methods can be further subjected to formal analysis jointly considering material and social dimensions with the recently developed network analysis techniques, like bipartite and multi-level network analysis, and to discuss methodological challenges in such complex research designs.

Papers addressing any other issues in network analyses of sociomateriality are also very welcome.

Statistical Network Modelling
Invited speaker and chair:
Peng Wang, Swinburne University of Technology

Invited speaker:
Christoph Stadtfeld, ETH Zürich
 

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 the 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.

Qualitative Network Analysis
Invited speaker and chair:
Elisa Bellotti, University of Manchester
 

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.

Technology and Innovation Networks
   

Systems of relations – and thus networks – can be considered as drivers of technological and innovative change. Well-known examples of successful technology and innovation in networks originated in the electronics industries of Silicon Valley in California and Route 128 in Massachusetts; machine-tool, apparel and tile industries in northern Italy; the machine-tools and automotive industries of southern Germany; and others. Experience of the innovation leaders has shown that multiple relational structures between organizations and individuals can provide high levels of diversity, and can be considered as the most favourable condition for knowledge creation, as well as for the emergence and development of innovations. Networks allow their members to get access to diverse information and competencies, enhance organizational learning capabilities, reduce costs, and minimise risks (De Man 2008; Malerba 2009; Johnson 2009).

Social network analysis allows to gain an understanding of how the ties allowing collaborative research, technological breakthroughs, and innovation emerge and develop (Rogers 1962; Valente 1995; Powell et al. 1996; Pyka & Küppers 2002; Burt 2005; Tortoriello & Krackhardt 2010). We invite well-grounded contributions based on the traditional social-network perspective that introduce new methods and techniques drawing on the established operationalizations.

Whereas social network analysis has mainly focused on social agents and their relations (Freeman 2004), the network approach to science, technology, and innovation studies (STI) has been multimodal from the beginning. In science studies, “networks of scientific papers” (Price 1965) are organized intellectually at the above-individual level into journals and disciplines; in technology studies, “selection environments” (Nelson & Winter 1982) induce technological trajectories and regimes; and in innovation studies, the focus is on the non-linear interfaces between R&D and markets.Can the transversal dynamics of innovation be modeled using network analysis? Multimodal networks of what components should be analyzed: words, people, or perhaps ideas? What is evolving in the dynamics of these networks: industries, routines, technologies, markets? How can these multimodal networks be operationalized, both in terms of their complexity as interfaces at each moment of time, and in terms of changing priorities over time? How are the emerging developments socially constructed, and how do the constructs feed back on the constructors themselves? What is the role of latent constructs such as regimes and disciplines? Papers dealing with these issues are particularly welcome.

Making Sense of Big Network Data: Testing Hypotheses on New Data
Chair:
Camille Roth, Humboldt University Berlin
 

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.

Particularly welcome will be papers (1) devoted to big data on relations between networks of different kinds – inter-personal, semantic, organizational, material objects, etc., - (2) applying to big data approaches that combine several networks, including multilevel, multiple or other combinations, as well as (3) using big data to compare networks across cultures, societies, states, economies, cities, - and so on.

Social Media Networks
Chair:
Svetlana Bodrunova, St. Petersburg University

Invited speaker:
Iina Hellsten, University of Amsterdam
 

The rise of social media enables online social networks. Social media has been considered as a virtual space for social interactions, but specific social media has also 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. This new social media data enables more varied approaches that combine social, content and meanings networks online. Such multimode networks pose new challenges for social sciences theories and methods.

This 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 big data, but also a theoretical understanding of societal problems and, not least, the associated 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.

Networks in Art: Practice and Structure, Meanings and Interactions
Chairs:
Aleksandra Nenko, NRU ITMO
Margarita Kuleva, 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 is also applicable to capture material embeddedness of artistic practice in immediate settings of studios (Farias & Wilkie 2016), local buzz (Currid & Williams 2009) and networked complexity of ‘creative’ city (Comunian 2011). Network analysis can also capture 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.

Papers also providing a comparative perspective with or between European societies. will be considered as especially relevant.

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

Since Lefebvre 2003 [1970] has announced ‘planetary’ urbanization, researchers are calling for new paradigms in theory and methodology to grasp city 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 Michael 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 underlayer of multiscale urban dynamics.

Second is assemblage theory and actor-network theory, which incline thorough investigation of sociomaterial configurations and non-human agencies in the 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 city through ‘grammars of gathering, networking and composition’ of different agents (p. 207). 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 explaining relations between diverse networks in 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 sequence 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 dynamics of city life.

We invite both papers that present comprehensive elaboration of theoretical assumptions, picking up networks as ontologies, and papers 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
Chair:
Artem Antonyuk, St. Petersburg University
 

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?

Among other widely discussed issues is the question of how multimodal data on policy networks may provide substantive insights into policy analysis. The main methodological problem concerns processing of multimodal network data and choice of appropriate network measures. The theoretical problems are the interpretation of the outcomes of multimodal data analysis in relation to the field of policy network research, and possible applications within other domains of political studies. The session particularly welcomes papers dealing with these problems as well as applications addressing topical issues of European societies.

Gender and Social Networks
Chair:
Elisa Bellotti, University of Manchester
 

Social network research studies the mechanisms that drive the formation of network structures as well as the outcomes of such structures on social behaviour. A well-investigated area of research focuses on gender differences in network formations and outcomes in personal and professional networks. Researchers have looked, for example, at the different styles of socialization of boys and girls at an early age, varieties of gendered network structures in different cultures, gender differences in peer networks and educational outcomes, gendered structural and cultural constraints of network strategies in organizational studies, different network positions and relational strategies between men and women at work, gender imbalance in academic networks and interlocking directorates.

This session wants to bring together interdisciplinary perspectives on gender similarities and differences in social networks which might be investigated with a variety of methods and modelling techniques. We welcome both highly quantitative modelling studies as well as qualitative research that looks at how discourses and narratives may impact the relational strategies embedded in network structures. We also welcome research that expand the very definition of gender to investigate peculiarities and differences of LGBT social networks.


Topics of the session might include, but are not limited to:

– Gender differences in structure and composition of personal networks;
– Gender differences in tie formation in early life;
– Gender dynamics in educational settings;
– Gender and social support over the lifetime;
– Gender, social capital and brokerage;
– Gender differences in interlocking directorates, academic networks and organizational studies;
– Gendered narratives in relational strategies;
– Gendered perceptions of SNA.

Literary Creation as a Product of Intellectual and Scientific Networks: Permeable Frontiers and Variable Nodes in European 19th Century
Chairs:
Charlotte Krauss, Université de Poitiers
Larissa Polubojarinova, St. Petersburg University
 

Apart from simple metaphorical uses, networks have only recently and rather timidly become an epistemological instrument in the humanities. In the area of comparative literature, which we would like to put at the center of our section, it is in particular for sociological and historical contextualization of literary research that network theory promises an exciting gain in knowledge. The different ways of use that begin to assert themselves can be reduced to two combinable approaches: Quantitative network analyzes have an obvious illustrative character, as a result of which graphic representations by means of Gephi and similar programs are increasingly being found in the humanities. Poetic networks, for example, can be captured in one graphic view at a glance and computer animation also makes it possible to understand their development over time. However, a deeper analysis of such networks requires the use of additional approaches. For their part, qualitative analyzes pose the question of the concrete method (apart from the classical description); moreover, they are subject to the dictate of feasibility and inevitably limit scientific studies to a few nodes and edges. This kind of reduction is also shown by the results of research groups explicitly ranged under the keyword "network", for example the volume Netzwerke des Wissens. Das intellektuelle Berlin um 1800 published in 2011 („Networks of Knowledge. Intellectual Berlin around 1800”, ed. by Anne Baillot, Berlin, BWV, 2011).

As part of our section, we want to make network theory fruitful for the analysis of relations between literary production and (philosophical) scientific reflection in the 19th century. Especially in the age of a still young research in humanities, the boundaries between creative and intellectual production were particularly permeable. Friendships, correspondence, dual gifts, statements in newspaper articles, political commitment, as well as the salon culture adopted from the 18th century prove the lively exchange. At the same time, philosophical or scientific writings as well as novels or dramas become independent nodes in the intellectual network of the time. In order to capture the polyvalence of texts and people, especially in transnational, European dimensions, network analysis offers promising new possibilities. Concrete examples of section contributions include the emergence of fundamental texts for literary criticism in the group of Coppet (poets, philosophers, economists from various European countries around Madame de Staël in Coppet, Switzerland) or the European network of intellectual correspondence around the Russian writer Ivan Turgenev and its impact on literary production.

Scientific Networks: Understanding Various Research Fields
Chairs:
Daria Maltseva, Higher School of Economics
Dmitry Zaytsev, Higher School of Economics
 

Scientific networks studies have been developed in the areas of sociology of science, information science, scientometrics, and bibliometrics. These studies are characterized by a variety of initial data sources, methodological approaches, and techniques. Our session aims to demonstrate this diversity and comprehensive applicability of scientific networks studies to various scientific disciplines. We welcome papers covering the wide range of possible types of scientific networks measuring scientific communication, collaboration and fields’ development in social and natural sciences. The session will build bridges between scholars who study scientific networks in national, international, interdisciplinary, and other diverse contexts. Papers in the session are expected to encourage the future research by addressing various topics on scientific networks across time and space.

Games, Communities and Networks
Chairs:
Anna Shirokanova, Higher School of Economics
Denis Bulygin, Higher School of Economics
Ilya Musabirov, Higher School of Economics
 

Computer games are one of the naturally networked research settings. Graph representations are underneath relational part of game logics, and players use, appropriate, build on and extend these representations to express complex social relationships, crossing boundaries of the game, social media and offline world.

In this section we welcome:

– Qualitative, quantitative and mixed SNA studies of board and computer games, esports and related communities;

– Methodological reflections, practices and developments, related to SNA studies of games.

We expect contributions about research on every stage, from conceptualization and research designs to mature studies and hope to help build a constructive discussion space.

Networks in Education
Chair:
Mohammed Saqr, University of Eastern Finland
 

There has been considerable effort by the educational community to understand social and collaborative learning using network analysis. The efforts encompass interactions among learners, online resources and learning process. Significant progress has been achieved by providing educators with tools and methods to visualize, quantify and mine relations and interactions, map collaborators’ roles, rank important collaborators and forecast students’ future behavior or performance. Methods include quantitative network analysis, generative network models and visualization. Recently, calls to incorporate network analysis and temporality in learning analytics have become visible, since time is a central dimension of how learning develops, unfolds and influences learners. Therefore, such methods that could extend the current network analysis approaches and helps us understand the complex process of learners relations, interactions and learning processes.

Currently, there is an increasing curiosity in using network analysis in various domains and there is a growing volume of research on the methods of analysis, uses, and what insights can be gained in educational contexts. This session aims at research that addresses the role and methods of network analysis in educational contexts, including - but not limited to - the following themes:

– Network analysis in Education;

– Dynamic network analysis in Education;

– The impact of network analysis on educational societies;

– Network analysis on adaptive and personalised learning;

– Relations between network analysis and pedagogical theories, e.g., behaviourism, social learning, connectivism, social learning, etc;

– Generative network models in education;

– Information and knowledge modelling and spread;

– Software demo for analysis of learning networks;

– Innovative data collection, analysis or presentation methods.

Professional and Digital Networks of Post-Soviet Migrants: From Local Embeddedness to Global Connectedness
Chairs:
Anna Smoliarova, St. Petersburg University
Irina Antoshchuk, University of Amsterdam,
St. Petersburg University
Oxana Morgunova, University of Glasgow
Olga Bronnikova, Université Grenoble Alpes
 

Diverse migration flows from the former Soviet Union after 1991 inspired a wealth of studies of Russian-speaking population abroad. United by a common “historically-specific socio-cultural background” rooted in the postwar and late socialism period (Byford 2009: 55) and Russian language, these people are perceived and investigated as a distinct group of migrants. On the other hand, it is widely recognized that Russian-speaking population abroad is very heterogeneous and embraces “the whole repertoire of migrant groups and identities” (Pechurina 2017: 39). Arguing that Post-Soviet(ness) is a contingent and context-dependent category, which has particular meanings and unfolds differently in different circumstances, underlining its changeable and negotiable character, scholars increasingly adopt a relational approach, placing migrant practices and experiences, interactions and narratives as means and sites for (re)producing communities and identities at the center of analysis (Brubaker 2005, Mavroudi 2007, Jons 2015).

Relational approach combines the investigation of “the nature of relationships between and within diasporic “sub-groups” and their embeddedness in “different social and cultural contexts”, involved in their formation and transformation (Pechurina 2017: 31). Although network as a concept holds a prominent place in the migration studies (Budarick 2014; Tsagarousianou 2004), works on Post-Soviet communities abroad are characterized by insufficient attention to the structure of migration networks and rarely implement social network analysis (in comparison with presence of SNA in the transnational migration studies, see Bilecen et al. 2018; Ryan & D’Angelo 2018). Developing relational approach, our session seeks to compensate for this lack.

Focusing on networks of Russian-speaking migrants, we follow the epistemological manifesto of “the connected migrant” (Diminescu 2008; Leurs & Ponzanesi 2018). Therefore, our session seeks to analyze the meaning and content of relations in connection to their structure and across different contexts, from institutional to local, from national to global. The original contribution of the session also consists in examining migrant networking in professional activities (science, journalism, entrepreneurship, blogging) that represent a largely underexplored area in migration network studies. In particular, we are interested in the forms that knowledge and experience sharing takes in different contexts of offline and online networks, contributing to the research of digital media use among migrants.

The session will address the following issues: 1) departing from transnationalism and global communication studies, we seek to problematize the traditional home-host country and local/national/global divisions in migration studies, that are still powerful for imagining the context despite substantial criticism; 2) extending the logic of the relational approach and drawing on network society theory (Castells 2011, Sassen 2004), which views places as constituted through networks and flows of capital, people, resources that pass through, we treat contexts as contingent, interconnected and dependent on interactions in the network, as reconfigured and co-produced along with migrant networking.

Innovations in Social Network-Based Interventions
Chairs:
Sebastian Stevens, University of Plymouth
Arunangsu Chatterjee, University of Plymouth
 

According to Valente, network interventions are ‘the purposeful efforts to use social networks or social network data to generate social influence, accelerate behavior change, improve performance, and/or achieve desirable outcomes among individuals, communities, organizations, or populations’ (Valente, 2012: 49). The field of network-based intervention has seen tremendous progress and development in recent years with innovations in methods, technology, analysis, and application. This session will offer a forum to present innovations in network data collection methods or tools, sampling approaches, incentives, intervention targets or topics, data analysis, network visualization, and use of technology for network-based interventions. Unique applications of networks within broader interventions are welcome, as are both personal, organisational and sociometric network interventions.

Interested participants are invited to submit theoretical, methodological or empirical papers, describing innovative intervention approaches in ALL fields. We particularly welcome approaches related to the fields of healthcare, implementation science, impact assessment, and innovation and entrepreneurship.

Students and Networks
Chairs:
Valeria Ivaniushina, Higher School of Economics
Vera Titkova, Higher School of Economics
Ilya Musabirov, Higher School of Economics
 

Students’ networks are vital both in school and in university context. Network analysis is widely used in educational and youth studies, especially for assessing peer influence on academic performance and health risk behavior. Numerous researches are focused on both positive and negative outcomes of peer influence. Negative peer effects may have severe adverse consequences, while positive peer influence leads to academic success, engaging in extracurricular activities, civic participation. We are looking for a diverse set of papers to balance research on school and university, online and offline networks of adolescents and young people.

Possible topics may include, but are not limited to:

- networks and academic performance;

- networks and risk behavior (drinking, smoking, drug use, eating disorders);

- interventions for reducing risk behavior through working with peer networks;

- structure of youth social networks in different settings;

- moderating factors in peer influence;

- youth behavior on social networking sites;

- online social networks of students;

- role of peers in online and blended learning.

A Critical Look on Globa-Net-Lization of Economic, Social and Political Context
Chairs:
Martin Koch, Bielefeld University
Alexander Kuteynikov, St Petersburg University
 

The purpose of the session is to critically discuss the objective and subjective factors that form the "context" and "basis" of network structures in economics, politics and social life.

At this session, we are planning to analyze the relationship of different spheres of life, in those aspects that are associated with network structures. In particular, we would like to draw our attention to how the network relationships and network interactions in the economy are formed and how economic networks determine the configuration of political institutions, legal complexes, ideological concepts, and international organizations.

We envisage an interdisciplinary discussion on the following subjects. What is the role of economic factors in the creation of political, social, ideological networks?

Are national and global institutions being formed as hybrid networks or do they remain classical hierarchical institutions? How the local, the national and the global are woven into a single network? How are global, national and local phenomena and processes related? Do network structures replace the "classical" hierarchical organization, or are they just another projection of it? Which economic, social and political players will dominate in globalized networks?

This will be a continuation of the discussion started at NetGloW’18, with the expansion of topics.

Main subjects to be discussed:

– Networks in economics, politics, ideology;

– Hybrid net-structures, organizations and institutions;

–‘Net-lisation’ of international institutions and international law;

–Networks in the area of Human Rights protection.


Software workshops

Multilevel ERGM Analysis with MPNet
Teacher:
Peng Wang, Swinburne University of Technology
 

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: http://www.swin.edu.au/melnet

Network Visualization Tools
Teacher:
Camille Roth, Humboldt University Berlin
 

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.

Network Clustering and Blockmodeling
Teachers:
Vladimir Batagelj, University of Ljubljana,
Higher School of Economics,
University of Primorska
Anuška Ferligoj, University of Ljubljana,
Higher School of Economics
Patric Doreian, University of Ljubljana,
University of Pittsburgh
 

Blockmodeling seeks to cluster units in a network which have substantially similar patterns of relationships with others, and interpret the pattern of relationships among clusters.The goal of blockmodeling is to reduce a large, potentially incoherent network to a smaller comprehensible structure that can be interpreted more readily. Blockmodeling, as an empirical procedure, is based on the idea that units in a network can be grouped according to the extent to which they are equivalent, according to some meaningful definition of equivalence.

In the workshop the undirect and direct approaches to blockmodeling will be presented with several examples. Also the generalized blockmodeling, pre-specified blockmodeling and blockmodeling of valued networks will be discussed.

For the blockmodeling of selected networks programs Pajek and R will be used. Therefore, it is recommended that the participants install them on their computers (http://mrvar.fdv.uni-lj.si/pajek/, https://www.r-project.org/). The workshop materials will be available at https://github.com/bavla/bm .

Recommended literature:

Patrick Doreian, Vladimir Batagelj, Anuška Ferligoj: Generalized Blockmodeling. Structural Analysis in the Social Sciences. Cambridge University Press, 2005.

Wouter De Nooy, Andrej Mrvar, Vladimir Batagelj: Exploratory Social Network Analysis with Pajek; Revised and Expanded Edition for Updated Software. Cambridge University Press, 2018.

Patrick Doreian, Vladimir Batagelj, Anuška Ferligoj (Eds): Advances in Network Clustering and Blockmodeling. Wiley, 2020.

Vladimir Batagelj, Andrej Mrvar, Anuška Ferligoj, Patrick Doreian: Generalized Blockmodeling with Pajek. Metodološki zvezki, 2(1), 2004, 455-467.

Semantic Network Analysis with Automap and ORA
Teacher:
Artem Antonyuk, St. Petersburg University
 

This practice-based workshop will introduce semantic network analysis – a method for studying textual data using techniques and insights of network analysis. Participants will learn how to conduct data analysis using specialized software.

First, the workshop will cover semi-automatic preprocessing of raw texts in Automap. Participants will learn how to create and apply delete lists and thesauri, remove noise words and phrases, and apply word stemming.

Secondly, participants will learn how to create semantic networks from preprocessed texts and how to choose appropriate parameters for network generation.

Third, participants will learn how to visualize and analyze semantic networks in ORA-LITE. They will learn how to visualize semantic networks, how to measure importance of words in a semantic network and how to qualitatively interpret network visualizations.

Target audience: The workshop is targeted towards people with no or moderate experience with text and network analysis.

Requirements: Participants are required to bring laptops with Automap and ORA-LITE installed (http://www.casos.cs.cmu.edu/projects/automap/software.php; http://www.casos.cs.cmu.edu/projects/ora/software.php). Automap and ORA-LITE are not available on MacOS, but can be run using virtualization software (Parallels, VirtualBox, Boot Camp).

The workshop duration is four hours.