[3B4-E-2] Machine learning: social links

[3B4-E-2-02] A Community Sensing Approach for User Identity Linkage

〇Zexuan Wang¹, Teruaki Hayashi¹, Yukio Ohsawa¹ (1. Department of Systems Innovation, School of Engineering, The University of Tokyo)

Keywords:User Identity Linkage, Network Embedding, Clustering

User Identity Linkage aims to detect the same individual or entity across different Online Social Networks, which is a crucial step for information diffusion among isolated networks. While many pair-wise user linking methods have been proposed on this important topic, the community information naturally exists in the network is often discarded. In this paper, we proposed a novel embedding-based approach that considers both individual similarity and community similarity by jointly optimize them in a single loss function. Experiments on real dataset obtained from Foursquare and Twitter illustrate that proposed method outperforms other commonly used baselines that only consider the individual similarity.