Programme

Sessions

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

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

 

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:
Johan Koskinen, University of 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 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.

Making Sense of Big Network Data: Testing Hypotheses on New Data
Chair:
Camille Roth, CNRS / 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
 

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
Co-chairs: Aleksandra Nenko and Margarita Kuleva

 

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.

Practices of cumulative deliberation in online networks
Chair: Svetlana S. Bodrunova, St. Petersburg University
 

Today’s public spheres are networked – and, along with this, are considered dissonant (Pfetsch, 2018), dissipative, disruptive, and discontinued. Networked deliberation (Bruns, 2008) is characterized by growth of complexity due to variances in users’ motivation and levels of institutionalization, which lowers predictability of political consensus so much sought for in traditional deliberation theory.

Moreover, with the growth of online discussions on social networks, the bulk of public discussion now belongs to a networked user, not to institutions, and his/her ‘tiny acts of political participation’ (Margetts et al., 2018) – posts, likes, reposts, comments, and mentions, which may also be considered elementary communicative actions (Habermas, 1990). These tiny communicative actions are rarely deliberative – that is, consensus-oriented, rational, inclusive, adjusted to the rules of round-table elaboration of decisions, and respectful to the other. Instead, they are emotional, interest-pursuing, based on personal experience, sometimes aggressive – that is, human.

Not only the nature of users’ tiny acts of communication but also the patterns of interaction online call for reconsideration of how we see today’s deliberation. We argue that it has not the dialogical but cumulative nature, where winning comes by tug-of-war-like cumulation of opinion. The spiral of silence (Noelle-Neumann, 1980) and silent majority effects, echo chambers, ad hoc and affective publics (Papacharissi, 2015) and many other phenomena in online discussions are cumulative by nature.

This ‘return to human’ in the deliberation studies deserves a ‘new normativity.’ First, one needs to acknowledge the right of a user to be irrational, emotional, non-purposeful, and one-sided. Second, in cumulative terms, each like matters: all the tiny acts are important for opinion crystallization. Third, on the level of a discussion network, dependencies of deliberation upon platform affordances, media presence, and outer context need to be taken into consideration. Fourth, network structures are crucial for opinion formation and constellating publics. Thus, the session welcomes the abstracts on cumulative effects in networked communication. This may include but is not limited to interplay between network structures and/or dynamics and discussion features, opinion cumulation in online networks and its thresholds, cumulative nature of networked publics and formation of ad-hoc discussion arenas, dynamics of social divisions and political polarization, tracing micro-cumulative effects like micro-spirals of silence or micro-shifts of agendas, and assessment of platform affordances in their relation to opinion growth.

Networks, Culture, Interaction
Chair: Jan Fuhse, Technical University Chemnitz

Invited speaker: Justus Uitermark, University of Amsterdam
 

Relational sociology conceptualizes social networks as interwoven with culture and as negotiated and changing in interaction. The session gathers presentations that follow this lead and investigate the connections of social networks with culture and / or interaction, both conceptually and empirically. Starting with the work of Harrison White, relational sociology has come to treat networks not as a-cultural structures, but as patterns of relationships that variously build on, and incorporate cultural forms (Emirbayer / Goodwin 1994; Fuhse 2009; Pachucki / Breiger 2010; Mische 2011).

In turn, culture is diffused and negotiated in social networks. We can examine this interplay in three ways (McLean 2017):

– Culture affects networks patterns, when these follow institutionalized roles, social categories, or models for social relationships (e.g., love, friendship, caste, patronage)

– Networks make for the diffusion and reproduction of cultural forms. This results in the stabilization of socio-cultural constellations with cultural beliefs and life-styles resting on cohesive network clusters, and with cultural differences between these

– Networks are themselves infused with meaning, with identities connected to each other through narratives, with network positions corresponding to social roles, coming with particular communication styles.

These advances have recently fed into the socio-semantic networks approach (Roth / Cointet 2010; see the Poetics Special Issue, 2020). Here, patterns of meaning are studied in their interrelation with networks of social relationships.

In a second line of research in relational sociology, social networks have been dissolved into processes of interaction, and reconstructed as patterns in this process (McFarland 2001; Gibson 2005; Mützel 2009; Kitts 2014; de Nooy 2015; Fuhse 2022). In this approach, social relationships and networks consist of regularities in communicative events, stabilizing, reproducing, and changing over their sequence. Rather than studying networks as clear-cut, stable arrangements of ties, we have to observe the sequential and relational ordering of communicative events (Butts 2008; Kossinets / Watts 2009; de Nooy 2011. This can entail (a) discerning relational micro-dynamics like reciprocity, transitivity, and preferential attachment that make for the tendencies to form different kinds of network patterns. (b) We can examine the network as the distribution of events by ties changing across time periods (e.g., Papachristos 2009). (c) The cultural imprint of processes in networks and the negotiation of identities and relationships can be studied qualitatively, with a focus on signals, vocabularies, communication styles, and other linguistic forms (McLean 1998; Mische 2008).

A wide variety of conceptual, methodological and empirical contributions is invited for the session. Presentations can focus on the nexus of networks and culture (including socio-semantic networks), on the interplay of networks and interaction, or they can relate to both of these themes.

Kinship Networks: at the Crossroads of Migration, Technologies and State Policies
Chair: Irina Kretser, St. Petersburg University  

The aim of this session is to analyze the linkage between kinship and cultural, political and legal orders.

For in recent decades, migration studies move away from research migration of people from point A to point B to research transnational social space and practices of “in-betweeness” life. Geographical distance between relatives impacts on ways that kinship networks create, maintain and transform. Traditional kinship networks are replaced by new care constellations which blur the boundaries between immediate and extended relatives, relatives and friends, local and translocal relatives. Flows of remittances, goods, emotions and information permanently cross the borders which result in emergence of transnational socio-material networks. Obviously, such networks do not remain unchanged over time but there is still a small amount of research on this issue.

New information and communication technologies connect us at a distance and radically change the forms of kinship communication. Polymedia (Madianou, Miller 2012) is a new space in which we are constantly surrounded by a large number of different types of media and make a choice between them. Which of the relatives will we talk to on the phone, and to whom would we prefer to send a text message? In which messenger will we discuss just work issues? Which platform is more suitable for quarreling? New norms and practices arise when kinship networks intersect with social networks and new media are constantly replacing the old ones. However, it is not only information technology that invades the territory of kinship relations. The assisted reproductive technologies represent interesting case for social network analysis: different actors such as potential parents, sperm/egg donors, surrogate mothers and doctors form a temporary social network to conceive and carry a child. But what happens to this network after the birth of a child? Who are relatives in these cases?

State and kinship are also inseparable from each other. Migration and family reunification policies, court decisions, and laws affect not only the size and composition of certain kinship networks but also the meanings of such notions as “family”, “marriage”, and “parenthood”.

We welcome papers on topics relating to, but not limited to:

– Transnational kinship networks;
– Kinship networks and “circulation of care” (Baldassar, Merla 2015);
– Kinship and support networks;
– Strong or weak ties in kinship networks;
– Kinship networks and ICT;
– Kinship networks and “ambient co-presence” (Madianou 2016);
– Kinship networks and assisted reproductive technologies;
– Family policies / Family reunification policies in different countries;
– Bureaucratic kinship: papers, certificates, DNA tests;
– Dynamics of kinship networks over time and space;
– Longitudinal analysis of kinship networks.

Literary Networks of the Long 19th Century: Sustainability and Dynamics on the Micro and Macro Levels
Chair: Larisa Poluboyarinova, St. Petersburg University  

As a time of intensive development and consolidation of social networks in the modern sense of the word (Randall Collins, Jürgen Osterhammel), the 19th century, especially its second half, became an age of substantial activation and qualitative growth of literary communication on the international level. As separate, albeit overlapping, networks, function for example editors of thick magazines, publishing house owners and professional translators, whose task as cultural intermediaries in the context of Goethe's 1827 proclamation of the era of "world literature" (Weltliteratur) takes on a special dimension, contributing to the creation of a pan-European literary field. Not only the contents of the pan-European or national history, but also the elements of artistic form become a communicable and transferable substance in the context of this field.

Based on the chronological framework of the long 19th century (E. Hobsbaum), i.e. 1789-1914, the section has as its task to trace a broad scale of sustainable network-like structures in literary communication in the context of a single national-literary field or beyond its borders. The focus of attention should be on the communication networks of authors, publishers, translators and readers, as well as on the network-like poetologically relevant commonalities, which can be singled out on the basis of the traditional analysis of historical poetics due to the common genre or common materials and motifs. An extra branch in the study of the lasting sructures of the long 19th century are undoubtedly literary transfers capable of forming new networks based on the reception of a work or an author in a diverse national-linguistic context, as was the case, for example, with the active reception of Henrik Ibsen's and Emile Zola's works throughout Europe and the United States. With the episteme of the network and the methodology of network analysis, it is hoped to expand and deepen this taxonomy considerably, to present this community of cult writers and their followers and admirers in other countries as a network construction with nodes and connections, thus freeing this material from the traditional comparatist rhetoric of "connections and influences". Contributions are welcome that work with both big data and limited material. Methodologically, a wide range of approaches is expected, from complex multiple graph analyses to qualitatively relevant interpretations of only single selected network segments.

Network Analysis for Learning: Actionable Insights
Co-chairs:
Mohammed Saqr, School of Computing, University of Eastern Finland
Sonsoles López-Pernas, ETSI Sistemas Informáticos, Universidad Politécnica de Madrid
 

A significant volume of research has addressed learning and learners’ behavior with network analysis. Many recent advances in network analysis in education have been partly kindled by the growing interest in learning analytics. Such efforts encompass a large variety of applications, e.g., interactions among learners, interactions with learning resources, and mapping friendship networks, to mention a few. Significant progress has been achieved that helped educators with tools and methods to visualize, quantify and mine relations and interactions, map collaborators’ roles, rank important actors, and forecast students’ future behavior or performance.

Since time is a fundamental dimension of how learning develops, unfolds and influences learners, calls to incorporate temporality have become recently visible. Dynamic network analysis could augment our current understanding of the complex process of learning, and of how and when important events occur. Several other novel applications of networks in education have emerged in the last decade and we have witnessed the birth of new sub-fields of networks in education and beyond, e.g., psychometric networks and epistemic network analysis. However, such growth brought several challenges and questions. Therefore, this session aims at opening the discussion about the latest developments, the challenges, as well as the methodological innovations in the field of networks in education.

Possible discussion topics include:

– Latest developments or applications of network analysis in education
– Innovative data collection, analysis or presentation methods
– Temporal networks, and temporal aspects of networks in general
– Ethical aspects of using networks in education
– Psychological networks in education
– Generative network models
– Software demonstration for analysis of learning networks
– Issues of methodological rigor, reporting and impact

Networks of International and Supranational Gamblers
Co-chairs:
Martin Koch, Bielefeld University,
Alexander Kuteynikov, St Petersburg University, associate researchers at ZDES/CGES
 

More than 40 years ago Harold Jacobson published his famous book “Networks of interdependence: international organizations and the global political system” (New York: Knopf, 1979). Since then, the number of states increased to 200, intergovernmental structures have exceeded 7,000 and the number of non-governmental organizations acting in world arena is far beyond 30,000. Also the forms of organizing world politics as well as methods to study them have changed significantly.

The session welcomes researchers to present and discuss how the world community is organized and structured, what new trends have appeared in grouping and interaction between international and supranational actors by analyzing three core dimensions of actors: inner world, external environment and their contributions to organize world politics from the standpoint of network analysis and sociological approach.

The discussion will be focused on following questions: what forms of interrelations dominate between actors in international relations and world politics: causal, network, functional or other? Is the hierarchy of world gamblers changing? Are networks genesis and development social in nature, or are these politically organized programs and projects? What is the balance between state, non-state and supra-state characteristics of networks? How to study and how to measure the network parameters in international and supra-national levels? What are opportunities and limits of network analyses and sociological approach to international and supranational phenomenon and processes.

Other topics are also welcomed.

The core of the speakers of the session will be formed by the members of Russian-German team of current project «A Theory on World Entities: Dynamics in Inner World, External Context and Roles in Organizing World Politics» (funded by DFG/RFBR).

Colleagues from Russia, CIS countries, Germany, Finland, and the Netherlands also will be invited.

Software workshops

Mixed Methods Research into Social Networks
Teacher:
Betina Hollstein, University of Bremen
 

The workshop focuses on the use of mixed methods research designs when studying whole and ego-centered social networks.

In the first part social network qualitative research and the principles of mixed methods research designs and its contributions to the study of social networks are introduced, pointing out advantages and challenges of this approach. Examples of mixed methods networks studies from a variety of fields of research are presented, including job mobility and organizational research. The second part focuses on mixed methods network data collection, including the use of visual tools.

Network Data
Teacher:
Ulrik Brandes, ETH Zürich
 

Viewing networks as a particular form of data rather than as phenomena greatly facilitates the selection and adaptation of methods in applied research.

We will identify the key characteristics of network data, from social structures and personal networks to dynamic networks and relational events, and discuss implications for issues ranging from measurement to visualization. The complementary roles of theory and method are illustrated on practical examples and software tool visone [https://www.visone.info/] is introduced along the way.

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) and Auto-Logistic Actor Attribute Models (ALAAM) with MPNet – a software developed to investigate the structural features of networks and how such structure may affect individual outcomes.

The workshop will start with a brief introduction to the overall logic of estimating (single-level) ERGMs/ALAAMs before introducing the recently developed multilevel ERGMs/ALAAMs. 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 also demonstrate how to user MPNet to model temporal network dynamics using Temporal ERGMs.

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.melnet.org.au/pnet

Network Visualization Tools
Teacher:
Camille Roth, CNRS / Humboldt University, Berlin
 

This workshop aims at presenting and illustrating the wide variety of approaches for the visualization of networks -- 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 techniques.

The goal is to equip participants with a critical feeling of the underlying assumptions made by a particular approach, 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 approaches:

- All-Purpose Layouts.

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 remain widespread). On the side of text mining, we would shed some light on the Natural Language Processing (NLP) assumptions and methods that make it possible to build networks from text content and to represent semantic networks.

- Specialized Approaches.

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 dependencies in social space, geographical space, and temporal space
Teacher:
Johan Koskinen, University of Melbourne
 

Statistical analysis of social network data is becoming increasingly popular and is progressively adding new substantive insights to the literature. The intricate contingencies of social relations in networks that have been the key focus of network research – such as triadic closure – are also what make statistical analysis of networks more involved than standard statistical analysis. In particular, these contingencies vitiate standard assumptions of independent observations. However, the explicit modelling of these dependencies is the express purpose of some statistical models for networks. Here we deal with two such modelling frameworks. This workshop will introduce exponential random graph models (ERGM) and stochastic actor-oriented models (SAOM) for analysing network data.

A general introduction to statistical modelling of ties in a network will be presented and the use of ERGM and SAOM will be exemplified with application of these models to a number of example data sets. These quick hands-on demonstrations will use MPNet, and the R-packages statnet and RSiena, and to get the most out of these exercises it is recommended that you bring your own laptop with these programmes installed. The overall aim is to provide a overview and working handle on how the principled consideration of how the basic interdependencies of relational ties extends to physical and temporal space. Some basic familiarity with social network analysis will be helpful.

MPNet program and manual: http://sna.unimelb.edu.au/PNet

Statnet tutorial: www.jstatsoft.org/article/view/v024i09/v24i09.pdf

Comprehensive RSiena manual (and additional resources): https://www.stats.ox.ac.uk/~snijders/siena/

A useful tutorial on SNA in R: http://www.bojanorama.pl/snar:start

Creating and analysing scientific networks A hands-on activity using open-access citation-metadata
Teacher:
Bilal Hayat Butt, DHA Suffa University
 

Researchers build new work on their own or others past work. It is attributed through the use of citations. It is one of the primary forms of acknowledgement for past work and thus acts as a form of measurement. Along with citations, other measures also exist such as social media attention, views and downloads of the article. However, amongst these measures citations are the least possible to malign. Even though self citations at the level of an individual or publisher are sometimes critiqued, it exists as a valid form of recognition. Scientists use the citation indexes such as WoS, Scopus or Google Scholar to analyse the research landscape within their domain. Science of science relies on citations from published research to gauge the scientific impact of past research. It is primarily done through proprietary bibliographic data sources of WoS or Scopus and other commercially available tools such as Dimensions, LENS or MAG.

Google Scholar, although free to use, is highly critiqued for indexing all the material over the internet. Also, it doesn't provide public access to its data. However, another bibliographic data source exists, namely, Crossref with over a billion citation links of registered DOIs. It is available as a public API upon which numerous commercial tools are built. It has over 85% citations as open-access in 2021 starting from 1% in 2017. It was mainly possible after the I4OC. This provides a great opportunity to work with a reliable data source that has publisher provided metadata. However, its API access is not intuitive for all. This workshop provides a scripted interface to access Crossref metadata for analysing scientific networks supplemented with OpenCitations. The workflow details creation of heterogeneous scientific networks, as well as its analysis. Datasets used are available to download from their respective websites.

This activity will be beneficial for early career researchers. A basic understanding of social network analysis will help, however, some introduction will be provided. Participants are required to bring their laptops with Python 3.9 installed. Few open-source libraries will be used (snap-stanford, pandas, DASK). The libraries can be installed using pip. Detailed instructions about installation will be provided prior to the workshop. Tentative topics include creating and analysing scientific networks (article citation network, author citation network, author collaboration network, co-citation network, bibliographic coupling), working with Crossref API, working with OpenCitations, centrality measures (degree centrality, betweenness centrality, closeness centrality, eigen centrality, PageRank). All topics will cover theoretical introduction as well as practical application using Python scripts from [1-4].