Social media privacy management strategies: A SEM analysis of user privacy behaviors

Abstract

Artificial intelligence (AI) is widely used in social network as AD Recommender Systems, Viral Marketing, and User Sentiment Detection. However, such things as Fake News and Privacy Leaking may violate privacy and security concerns. AI technology is also often used in social media as the main technology to prevent personal privacy from leaking. This study explored whether social media users will disclose information or further protect privacy when facing information privacy issues. It studied information security awareness and perceived privacy control while affecting privacy concerns and customer calibration related factors, and finds their privacy management and self-disclosure. This study used questionnaire survey method to understand user data and used Structural Equation Modeling (SEM) to analyze the relationship of various dimensions. The results showed that understanding information security awareness and customer alienation through AI technology has a positive impact on consumers’ privacy concerns. Through privacy management, consumers can indeed reduce their doubts about privacy leakage. Customer privacy concerns and customer calibration have positive and significant effects on privacy management and self-disclosure, respectively. This study showed that user trust in the platform will affect the degree of user information disclosure. The industry should focus more on the user’s privacy maintenance and establish a complete protection mechanism.