A Survey of Across Social Networks User Identification

• Main Authors: Ling Xing, Kaikai Deng, Honghai Wu, Ping Xie, H. Vicky Zhao, Feifei Gao
• Format: Article
• Language: English
• Published: IEEE 2019-01-01
• Series: IEEE Access
• Subjects: Big data; across social networks; user identification; entity user
• Online Access: https://ieeexplore.ieee.org/document/8846206/

With the popularization of the Internet and the arrival of the big data era, numerous different social networks (SNs) have emerged to satisfy users' social needs and offer them rich content and convenient services. Under these circumstances, identifying multiple social accounts belonging to the same user across different SNs is of great importance for many applications. Across social networks user identification (ASNUI) can help perfect user information, offer personalized service recommendation, and data mining, as well as provide support for scientific research. This paper first systematically introduces the application of ASNUI in the field of social computing, then states its applications and challenges, and reviews the adopted models, frameworks, and performance comparison state-of-the-art techniques used in ASNUI. Finally, we also identify a few future research directions in ASNUI, such as weight allocation of user attribute information, the fusion of multi-dimensional information, and large-scale user identification.