Understanding User Continuance Intention Toward AI-Driven Social Media Platforms: The Mediating Role of Attitude and Satisfaction - Adele Mailangkay; Dedy Syamsuar; Yulia Ery Kurniawati (Jurnal Nasional Pendidikan Teknik Informatika: JANAPATI, 2026)
Artificial Intelligence (AI) is influencing user engagement, interactions, and perceptions on social media. The purpose of this study is to understand the user’s purpose, with the aim of determining which of the various factors linked to the user’s intention of continuing to use AI social media applications, while focusing on the role of attitude and user satisfaction as the mediators. The study used 532 responses of social media users for the purpose of this study. The study used the following seven constructs: AI Trust, Algorithmic Transparency, Information Quality, Performance Expectancy, Attitude, User Satisfaction, and Continuance Intention. A total of 532 valid responses were analyzed using PLS-SEM to demonstrate that the results indicate that Performance Expectancy significantly influences user attitude, while Information Quality indirectly affects attitude through Performance Expectancy. However, AI Trust does not have a significant effect, and Algorithmic Transparency shows a negative effect on attitude. User attitude and user satisfaction positively and significantly affect the intention to continue using, or what is termed the positive mediating effect of user attitude and user satisfaction. The results provide insights into the role of performance-driven factors in AI adoption, suggesting that improving system functionality, content relevance, and user experience is more critical than emphasizing trust and transparency in AI-driven social media environments.