Embeddings of Nation-Level Social Networks

Fuente: arXiv

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Bibliographic Details
Main Authors:	Pial, Tanzir, Hafner, Flavio, Handzlik, Dakota, Hassan, Enamul, Sage, Lucas, Macanovic, Ana, Emery, Tom, van de Rijt, Arnout, Skiena, Steven
Format:	Preprint
Published:	2026
Subjects:	Social and Information Networks Networking and Internet Architecture
Online Access:	Acceder al recurso
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_version_	1866910087927300096
author	Pial, Tanzir Hafner, Flavio Handzlik, Dakota Hassan, Enamul Sage, Lucas Macanovic, Ana Emery, Tom van de Rijt, Arnout Skiena, Steven
author_facet	Pial, Tanzir Hafner, Flavio Handzlik, Dakota Hassan, Enamul Sage, Lucas Macanovic, Ana Emery, Tom van de Rijt, Arnout Skiena, Steven
contents	Full nation-scale social networks are now emerging from countries such as the Netherlands and Denmark, but these networks present challenging technical issues in working with large, multiplex, time-dependent networks. We report on our experiences in producing dynamic node embeddings of the population network of the Netherlands. We present (a) a layer-sensitive random walk strategy which improves on traditional flattening methods for multiplex networks, (b) a temporal alignment strategy that brings annual networks into the same embedding space, without leaking information to future years, and (c) the use of Fibonacci spirals and embedding whitening techniques for more balanced and effective partitioning. We demonstrate the effectiveness of these techniques in building embedding-based models for 13 downstream tasks.
format	Preprint
id	arxiv_https___arxiv_org_abs_2603_29059
institution	arXiv
publishDate	2026
record_format	arxiv
spellingShingle	Embeddings of Nation-Level Social Networks Pial, Tanzir Hafner, Flavio Handzlik, Dakota Hassan, Enamul Sage, Lucas Macanovic, Ana Emery, Tom van de Rijt, Arnout Skiena, Steven Social and Information Networks Networking and Internet Architecture Full nation-scale social networks are now emerging from countries such as the Netherlands and Denmark, but these networks present challenging technical issues in working with large, multiplex, time-dependent networks. We report on our experiences in producing dynamic node embeddings of the population network of the Netherlands. We present (a) a layer-sensitive random walk strategy which improves on traditional flattening methods for multiplex networks, (b) a temporal alignment strategy that brings annual networks into the same embedding space, without leaking information to future years, and (c) the use of Fibonacci spirals and embedding whitening techniques for more balanced and effective partitioning. We demonstrate the effectiveness of these techniques in building embedding-based models for 13 downstream tasks.
title	Embeddings of Nation-Level Social Networks
topic	Social and Information Networks Networking and Internet Architecture
url	https://arxiv.org/abs/2603.29059