A Scalable Real-Time Chat System Using MERN Stack with Redis Optimization Sentiment Analysis

This paper presents a scalable real-time chat system de- veloped using the MERN stack, integrating Socket.IO for real-time communication, Redis for caching and message brokering, and an external API for sentiment analysis. The system addresses key challenges in modern communication applications, including latency, scalability, and efficient data handling. The implementation demonstrates that the use of Redis significantly reduces message delivery latency and minimizes database load by caching frequently accessed data and en- abling Pub/Sub-based communication. Socket.IO ensures reli- able and low-latency bidirectional communication, supporting essential features such as one-to-one chat, group chat, user presence tracking, and message status indicators. Experimental evaluation with concurrent users shows that the system maintains stable performance and efficient message delivery under load. The integration of sentiment analysis further enhances the system by providing intelligent insights into user interactions without affecting overall performance. Overall, the proposed system provides a robust, scalable, and efficient solution for real-time communication, making it suitable for modern web-based applications requiring high responsiveness and reliability.

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