In today’s digital era, social media platforms play a crucial role in branding, marketing, and communication. Managing multiple platforms such as Instagram, Facebook, LinkedIn, and Twitter (X) manually requires repetitive posting, separate scheduling, and fragmented analytics tracking, leading to inefficiencies and operational complexity. This paper presents the Intelligent Social Media Automation and Analysis System (ISMA), a full-stack web-based application that centralizes content creation, multi-platform publishing, scheduling, and analytics visualization. The system is developed using Node.js and Express.js with MongoDB for data storage, while Power BI is integrated for advanced analytics dashboards. Experimental evaluation demonstrates significant reduction in manual effort, improved scheduling accuracy, and data-driven decision-making efficiency. The proposed system contributes a unified architecture that integrates automation, scheduling precision, and business intelligence analytics within a scalable full-stack framework.

Dr.M.Jaithoon Bibi, Ms.V.Uthra, T.Kalaiselvi,"Intelligent Social Media Automation and Analysis System (ISMA)" International Journal of Advanced Multidisciplinary Research and Educational Development, V2(4): Page(19-25) March - April 2026. ISSN: 3107-6513. www.ijamred.com. Published by Scientific and Academic Research Publishing.