@inproceedings{aec3bef4bfae403da2fd7e6804a83545,
title = "Embeddings of Nation-Level Social Networks",
abstract = "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.",
keywords = "Clustering, DeepWalk, Demography Prediction, Graph embedding, Multiplex Networks, Population-scale social networks",
author = "Tanzir Pial and Flavio Hafner and Dakota Handzlik and Enamul Hassan and Lucas Sage and Ana Macanovic and Tom Emery and \{van de Rijt\}, Arnout and Steven Skiena",
note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.; 14th International Conference on Complex Networks and Their Applications, COMPLEX NETWORKS 2025 ; Conference date: 09-12-2025 Through 11-12-2025",
year = "2026",
doi = "10.1007/978-3-032-16719-4\_27",
language = "English",
isbn = "9783032167187",
series = "Studies in Computational Intelligence",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "332--344",
editor = "Hocine Cherifi and Rocha, \{Luis M.\} and Zeynep Ertem and Chantal Cherifi",
booktitle = "Complex Networks and Their Applications 14 - Proceedings of The 14th International Conference on Complex Networks and their Applications",
}