Embedding-aware Polarization Management in Signed Networks

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Authors: Jeonghan Son, Kyungsik Han, Yeon-Chang Lee
Cited by: 0

Abstract

Signed network embeddings (SNE) are widely used to represent networks with positive and negative relations, but their repeated use in downstream analysis pipelines can inadvertently reinforce structural polarization. Existing polarization measures are largely designed for unsigned networks or rely on predefined opinion states, limiting their applicability to embedding-based analysis in signed settings. We propose EPM, a unified polarization management framework that jointly measures and mitigates polarization in the embedding space. EPM introduces an embedding-based polarization measure grounded in effective resistance and a structure-aware mitigation strategy via localized augmentation through structurally balanced intermediary nodes. Experiments on real-world signed networks demonstrate that EPM effectively mitigates polarization while preserving task-relevant network structure. The codebase of EPM is available at https://github.com/JeonghanSon/EPM-Embedding-aware-Polarization-Management.

Fields of Study & Subjects

Advanced Graph Neural Networks Complex Network Analysis Techniques Opinion Dynamics and Social Influence

Publication details

Journal / source
arXiv (Cornell University)
Publication date
25 February 2026
Language
EN
Document type
Preprint