[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)

キーワード：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.