A Review of User Profiling Based on Social Networks

Abstract

The rapid development of the internet and smartphones has enabled people to access numerous information systems and large volumes of data. User profiling technology can meet the dual challenge of analyzing user characteristics, interests, or preferences and recommending corresponding resources. Nevertheless, the insufficiency and isolation of data in traditional information systems limit the effect of user profiling, and social networks can compensate for this deficiency. With massive quantities of data in text, images, videos, and relationships in social networks, user profiling can achieve highly accurate analytical results. This review comprehensively discusses user profiling for social networks, defines its criteria, and expounds on the entire process, from data collection to the profiling model and performance evaluation. It includes various models with advantages and disadvantages and corresponding application scenarios. Additionally, considering that technology serves humans, this review provides users with multiple applications in the industry for user profiling based on social networks. Furthermore, it discusses the ethical and legal issues associated with user profiling. Finally, this review highlights possible future research directions in this field. Overall, this review can help researchers enhance their understanding of the current state of research in the field of user profiling and gain ideas for further study.

Keywords

• Recommendation system
• social network
• user modeling
• user profiling