arXiv Open Access 2026

Embeddings of Nation-Level Social Networks

Tanzir Pial Flavio Hafner Dakota Handzlik Enamul Hassan Lucas Sage +4 lainnya

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Abstrak

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.

Topik & Kata Kunci

cs.SI cs.NI

Penulis (9)

Tanzir Pial

Flavio Hafner

Dakota Handzlik

Enamul Hassan

Lucas Sage

Ana Macanovic

Tom Emery

Arnout van de Rijt

Steven Skiena

Format Sitasi

APA MLA BibTeX

Pial, T., Hafner, F., Handzlik, D., Hassan, E., Sage, L., Macanovic, A. et al. (2026). Embeddings of Nation-Level Social Networks. https://arxiv.org/abs/2603.29059

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Informasi Jurnal

Tahun Terbit: 2026
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓