Privacy Protection on Social Media Platforms: Overdisclosure of Online Behavioral Data is Labeling Users

Abstract In the digital age, the protection of privacy and personal data on social media platforms has become increasingly significant. Online behavioral data includes user interactions, fandom affiliations, and engagement records, simultaneously encompassing both defensive privacy expectations and reasonable use expectations – blurring the lines between different levels of personal data protection. The sensitivity of online behavioral data, when aggregated, generates a “digital identity” that reflects a natural person’s social identity and is closely linked to individual personality, resulting in high identifiability and privacy risks. Due to the highly commercialized use of personal data by social media platforms and the ineffectiveness of the informed consent mechanism, legal frameworks primarily focus on traditional sensitive personal data, leaving the handling of online behavioral data inadequately regulated despite its potential to cause privacy risks. By analyzing consent mechanisms and case studies from platforms such as Weibo, this research highlights how default platform settings prioritize disclosure over user control and why current informed consent mechanisms are inadequate. This study advocates for a more comprehensive boundary delineation of sensitive personal data, a renewed stratification of personal data in the digital age, and stricter informed consent mechanisms to strengthen privacy protections, aligning platform regulations with contextual privacy expectations.