社交网络用户身份关联及其分析

同一用户在不同社交平台注册账号，使得用户数据分散于多个平台，且这些数据不全面、不可靠、利用率低.通过分析这些跨平台的数据，发现不同账户对应同一用户的真实身份，使跨平台用户身份关联，以构建详细的用户画像、推荐系统、跨社交网络的链接预测等.从国内外身份关联技术的研究现状出发，介绍了用户身份关联及分析框架，整理了身份数据采集标准和社交网络数据集；分析了近几年用户身份关联技术，并归纳了身份关联评价指标，阐述了基于身份关联的社交网络数据挖掘及分析框架；最后对身份关联中的研究难点及热点进行了讨论和展望.

Social Network User Identity Association and Its Analysis

The same user registers accounts on different social platforms, which makes user data scattered across multiple platforms, and these data are incomplete, unreliable and low utilization. By using these cross-platform data to discover the real identity of the same user corresponding to different accounts, cross-platform user identity association plays an important role in building detailed user profiles, recommendation systems, cross-social network link prediction and other cross-platform applications. Starting from the research status of identity association technology at home and abroad, the framework of user identity association and analysis is introduced, and the standards of identity data acquisition and social network data sets are collated. Subsequently, the technology of user identity association in recent years is analyzed and the evaluation index of identity association is summarized, and the social network data mining and analysis based on identity association is expounded. Finally, the research difficulties and hotspots of identity association are discussed and prospected.