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Institute for Advanced Study (IAS) Institute for Advanced Study (IAS)

Are social networks different to other types of networks? (online)

POPNET Connects with Jolien Cremers

In this seminar of the POPNET Connects series, Jolien Cremers, Senior Advisor at the Data Science Lab at Statistics Denmark, will discuss the creation of a registry-based, multi-layer, and temporal network of the entire Danish population from 2008-2021, covering approximately 7.2 million individuals. The network maps relationships formed through family, households, workplaces, and schools, providing insights into how social connections influence various aspects of life, such as career trajectories and health. Cremers will also explore how connections reappear across different life stages, reflect one's position in the income distribution, and reveal patterns in shortest path lengths between individuals, offering a novel approach to understanding societal dynamics.
Date
21 October 2024
Time
14:00 -15:00

Please register for the seminar via the button below. You will receive a confirmation via email.

Unveiling the Social Fabric: A Temporal, Nation-Scale Social Network and its Characteristics

Social networks shape individuals' lives, influencing everything from career paths to health. Statistics Denmark and Copenhagen Centre for Social Data Science developed a registry-based, multi-layer and temporal network of the entire Danish population in the years 2008-2021 (roughly 7.2 mill. individuals). Our network maps the relationships formed through family, households, neighborhoods, colleagues and classmates. Analysis of the network reveals how past connections reappear later in other layers, that the number of relationships aggregated over time reflects the position in the income distribution, and that we can recover canonical shortest path length distributions when appropriately weighting connections.

Jolien Cremers

About Jolien Cremers

Jolien Cremers is Senior Advisor at the Data Science Lab at Statistics Denmark. She is responsible for maintaining and developing the Danish Nation-Scale Social Network data as well as cooperating with outside researchers on projects that use this data. She obtained her Ph.D. in applied statistics for social science from Utrecht University in 2019. Her previous research was on Bayesian methodology for circular statistics as well as applied statistics for longitudinal models of health and other types of registry data.

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