International Research Journal of Education and Technology

The Indian government's need for effective, continuous observation and the management of public opinion across several regional dialects and sight and sound organizations is met by the suggested computer-based intelligence-driven input architecture. Understanding how emotions are conveyed through text, voice, and video information is essential for effective governance in a semantically diverse country like India, where local news sources shape public opinion. Through the use of AI and advanced natural language processing (NLP), the framework conduct’s opinion research across a variety of media outlets. It analyzes written material and interprets spoken words from audio and video sources, providing a comprehensive assessment of public sentiment. This interactive media sentiment analysis gives the public authority the ability to capture diverse perspectives from different places. The framework also organizes departmental organization and problem tracking, which groups news items by important government agencies. This ensures faster, more involved responses to emerging issues and works with assigned inquiry. Ongoing knowledge upgrades permit public authorities to take proactive measures when necessary by providing executives with timely warnings. Additionally, the framework monitors public engagement and criticism, providing additional insights into public opinion and dedication to government initiatives. It is easy to send and grow across several administrative divisions due to its lightweight design and intuitive point of interaction. This artificial intelligence-powered input system provides a cutting-edge solution for ongoing, multilingual opinion analysis and media monitoring tailored to the Indian government. In the current complicated media landscape, its ability to analyze visual and auditory content, monitor problems, and transmit continuous bits of information makes it an essential tool for management, emergency executives, and critical correspondence.

Key Words: AI-driven feedback system, real-time sentiment analysis, multilingual media monitoring, natural language processing (NLP), machine learning