User Interest Profiling Techniques for Targeted Web Advertisements: Leveraging Social Networking Data

These days, social networking sites play a major role in digital interactions. They produce vast amounts of data that may be utilized to create detailed user interest profiles. Understanding user behavior, customisation, and targeted advertising all depend on this process. This study offers a thorough analysis of the different methods for creating user interest profiles from social networking data, classifying approaches into four categories: behavior-based, content-based, network-based, and hybrid. We also examine the difficulties with profiling techniques, including scalability, data sparsity, and privacy issues. The study concludes by highlighting recent developments and possible avenues for future investigation in this field.