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Mobile Networks and Applications

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17.12.2019

A Two-Stagse Approach for Social Identity Linkage Based on an Enhanced Weighted Graph Model

verfasst von: Tao Qin, Zhaoli Liu, Shancang Li, Xiaohong Guan

Erschienen in: Mobile Networks and Applications | Ausgabe 4/2020

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Abstract

Social identity linkage refers to identify the accounts belong to the same person across different social networks. This work can assist in building more complete social profiles, which is valuable for many social-powered applications. In this paper, we propose a two-stage approach to improve the efficiency and accuracy of large-scale social identity linkage. The first stage deals with the seed set enrichment problem and focuses on exploring a larger set of seeds with greater precision. The second stage deals with the global propagation problem and focuses on finding more matched pairs with lower computation. Moreover, we propose an enhanced weighted graph model to deeply investigate the structural characteristics. We also develop an attribute representation method to reduce the impact of missing attributes. Finally, we evaluate our method based on the datasets collected from two popular social networks in China. And the experimental results demonstrate that our method outperforms other state of the art algorithms.

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Titel: A Two-Stagse Approach for Social Identity Linkage Based on an Enhanced Weighted Graph Model
verfasst von: Tao Qin
Zhaoli Liu
Shancang Li
Xiaohong Guan
Publikationsdatum: 17.12.2019
Verlag: Springer US
Erschienen in: Mobile Networks and Applications / Ausgabe 4/2020
Print ISSN: 1383-469X
Elektronische ISSN: 1572-8153
DOI: https://doi.org/10.1007/s11036-019-01456-8

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