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AI-Powered Social Media Analytics and Predictive Content Performance Optimization

Mirzayev BoburAlfraganus University, Tashkent, UzbekistanValisher SapayevR. N. RavikumarJain (Deemed to be) University, Bangalore, IndiaAzamat AbdurakhmanovTermez University of Economics and Service, Termez, UzbekistanS. AarthiMarwadi University, Rajkot, IndiaOtamurodova AzizaUrgench State Pedagogical Institute, Urgench, Uzbekistan
2026

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ABI

Annotatsiya

Artificial Intelligence has become a key facilitator of sophisticated social media analytics, and it is changing the content management perspective of performance monitoring, which is reactive, to being proactive and intelligence-based decision-making. The chapter focuses on social media analytics based on AI and predictive content performance optimization on the largest platforms. It relates to the application of machine learning, deep learning, natural language processing, and multimodal analytics to form engagement, sentiment, audience behavior, and content dynamics models. The chapter shows the uses of predictive intelligence in proactive content planning, optimization of campaigns and reputation as through conceptual framing and recent case-based evidence. It also deals with practical deployment considerations, integration into an organization and ethical governance issues. The chapter also ends with identification of upcoming research and managerial implications of responsible and performance-inducing AI-driven social media content management.

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