The embedding of social actors within physical spaces has been increasingly studied in Social Network Analysis. What has received less attention to date is a more dynamic perspective on the different kinds of spaces that actors flow through in their everyday lives, which have become more manifold and shifting, for example through hybrid working and digital technologies.

In this talk I want to explore a new perspective for the relationship between people and space by building on Ron Breiger’s seminal approach to the duality of networks, which considered how individuals intersected within groups by virtue of their participation in events. This can be applied to people and spaces. Practically, this means focussing on movement patterns, i.e., how people make their way from A to B, which path they chose, and therefore how often they frequented different spaces along the way.

This approach works across scales, but here two case studies are explored of space usage processes inside buildings: an in-patient ward and the variety of healthcare workers moving through it, and a university building populated by students and staff. Preliminary insights suggest that the particular patterning of the spaces an individual frequents tells us something about the individuality of the actor and their social embeddedness, and vice versa, which people use which spaces may tell us something about the character of those spaces.

This work hopes to widen perspectives on the context of social structures by offering a way of analysing dynamic actor-related behaviours in space.

Background and Aims: Connecting for Care is a mixed-method social network analysis case study of Canada’s child development and rehabilitation network. It explores social ties and knowledge translation (KT) patterns among healthcare providers, families, researchers, and KT support personnel. This presentation outlines our integration of algorithmic and geographic visualization approaches to facilitate analysis and qualitative data gathering.

Methods: A cross-sectional national online survey collected respondents’ KT connections across Canada’s 10 provinces and 3 territories. Using UCINet and NetDraw, we created egocentric maps showing inter/intra-provincial/territorial knowledge exchange patterns. Nodes were positioned manually by province/territory and region using WindowTop software to optimize clarity. These visualizations were presented during interviews to further our understanding of network structure and factors influencing tie development.

Results: We identified 596 connections among 622 individuals (234 respondents; 388 non-respondents). Analysis revealed 452 intra- and 144 inter-provincial/territorial ties, with connections concentrated in densely populated regions. We generated 13 provincial/territorial maps and 3 regional visualizations for interpretation. Average geodesic distance of 3.6 suggests relatively efficient knowledge exchange despite Canada’s vast geography. Knowledge brokers (betweenness centrality range: 0-1003, median: 0) were primarily concentrated in central Canada. Interview participants valued intra-provincial connections for exchanging context-specific information within Canada’s decentralized health system.

Conclusion: The predominance of intra-provincial ties reflects the importance of region-specific expertise and the opportunity to support the implementation of evidence-based practices across Canada. Qualitative inquiry enhanced our understanding of network structure. Software development that improves the integration of geographic and network data would facilitate this approach.

While migration patterns have traditionally been analyzed primarily through economic, security, and migrant community network frameworks, the growing impact of climate change necessitates a shift in focus to understand the role of climate factors in shaping these movements. This study explores the intersection of climate change and global migration patterns over the past two decades, focusing on South-to-North migration. Utilizing international migration data and satellite imagery, we employ valued Exponential Random Graph Models and spatial analyses to identify emerging migration hotspots linked to regions experiencing severe climate impacts. These geocoded migration networks highlight how climate stressors, such as floods, sea level rise (elevation change), and extreme temperatures, influence the magnitude and direction of migration flows. Our findings reveal significant shifts from traditional migration patterns, emphasizing how climate-induced stressors reshape the relational dynamics and migration pathways of these networks. By focusing on the spatial dimensions of climate-induced mobility, this study underscores the importance of geographic and climatic context in understanding migration networks. This study contributes to a more nuanced understanding of how environmental stressors shape network structures and offers valuable insights for understanding human mobility and fostering social cohesion across borders in a climate-impacted world.

The rapid deployment of green innovation is critical to achieving global carbon targets. Climate change mitigation technologies (CCMTs) produce a global public good, yet their R&D costs, risks, and benefits remain strikingly uneven. Over the past two decades, CCMT co-invention networks have evolved from core-periphery structures—dominated by the U.S., China, and Germany, into more polycentric systems where emerging economies like India play an increasing role (Ma et al., 2022). However, little is known about how these co-invention networks and their dynamics influence patent filing strategies and jurisdiction selection, and so their diffusion across the global market. This study leverages global patent data from PATSTAT, USPTO, and Lens.org, applying a relational event model to analyse the structural drivers of CCMT patenting decisions. We examine how inventor nationality, cross-country collaborations, and network topology (e.g., hub-spoke vs. distributed structures) shape patent jurisdiction choices. By unpacking the interplay between global co-invention networks and patenting decisions, this research offers insights into the strategic dimensions of green technology diffusion, market selection, and innovation drivers.

The emergence of online social networks like Facebook in the early 2000’s promised a breakthrough in social networks research social network research by enabling analysis of societal-scale interactions due to abundant data. However, despite many groundbreaking studies, progress has been limited by a lack of freely available data. In rare cases where such data have been made available by platforms to researchers, individual-level data can typically not be shared with the wider research community. However, data that are aggregated to higher social entities, such as municipalities, can be shared more easily. This paper presents one such data set based on the (now defunct) Dutch social network platform Hyves. From an underlying individual-level network covering a significant fraction of the population, we create a data set of consisting of topological features of within-municipality networks, covering all municipalities in the Netherlands. This provides a unique insight into features of social connectivity within municipalities that is not readily available from other resources. We present descriptives of topological features of municipality networks, explore associations with other properties of municipalities, and demonstrate the usefulness of municipality-level network measures for social research.