A Review of User Profiling Based on Social Networks
Wenbo Wu, Masitah Ghazali, Sharin Hazlin Huspi · IEEE Access · 2024
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 the form of 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 algorithms, application scenarios, and the advantages and disadvantages of these algorithms. Additionally, considering that technology serves humans, this review provides users with various applications in 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.