社交网络上的用户身份链接:现代技术与应用综述

Caterina Senette, Marco Siino, Maurizio Tesconi
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引用次数: 0

摘要

在在线社交网络(OSN)中,用户可以创建一个独一无二的公共个人信息,精心制作用户身份,其中可能包括个人资料、内容和网络相关信息。因此,人们感兴趣的一项相关任务与在不同的 OSN 之间链接身份的能力有关。跨社交网络链接用户在个人和群体两个层面都会产生多重影响。在个人层面,跨社交网络链接同一身份的主要目的是为了更好地了解每个用户。在群体层面,通过不同的 OSNs 链接用户身份有助于预测用户行为、网络动态、信息扩散和社交媒体间的迁移现象。将不同 OSN 上的用户账户绑定在一起的过程极具挑战性,在过去 15 年里吸引了越来越多的研究关注。这项工作的目的是全面回顾近期(2016 年至今)关于跨网络社交网络用户身份关联(UIL)方法的研究。本综述旨在通过概述该领域研究人员提出的主要问题表述、不同的特征提取策略、算法、机器学习模型、数据集和评估指标,为该领域的其他研究人员提供指导。本综述从务实的角度出发,强调了根据可用数据类型完成这项任务的具体可能性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
User Identity Linkage on Social Networks: A Review of Modern Techniques and Applications
In an Online Social Network (OSN), users can create a unique public persona by crafting a user identity that may encompass profile details, content, and network-related information. As a result, a relevant task of interest is related to the ability to link identities across different OSNs. Linking users across social networks can have multiple implications in several contexts both at the individual level and at the group level. At the individual level, the main interest in linking the same identity across social networks is to enable a better knowledge of each user. At the group level, linking user identities through different OSNs helps in predicting user behaviors, network dynamics, information diffusion, and migration phenomena across social media. The process of tying together user accounts on different OSNs is challenging and has attracted more and more research attention in the last fifteen years. The purpose of this work is to provide a comprehensive review of recent studies (from 2016 to the present) on User Identity Linkage (UIL) methods across online social networks. This review aims to offer guidance for other researchers in the field by outlining the main problem formulations, the different feature extraction strategies, algorithms, machine learning models, datasets, and evaluation metrics proposed by researchers working in this area. The proposed overview takes a pragmatic perspective to highlight the concrete possibilities for accomplishing this task depending on the type of available data.
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