Abstract: In response to the contemporary demands of a rapidly evolving media landscape, our innovative AI-driven feedback system emerges as a solution adept at assessing diverse media content across multiple regional languages. This cutting-edge approach addresses the critical need for real-time evaluation of government-related news, serving as a pivotal tool for monitoring public opinion and refining communication strategies. The absence of an AI-driven feedback system for evaluating government-related news in regional languages presents a substantial challenge. Our solution becomes indispensable in proactively managing public opinion, facilitating crisis response, and fostering effective communication. It accomplishes this by tracking sentiment in regional media and categorizing news by department, offering a lightweight prototype that seamlessly integrates sentiment analysis, issue tracking, and public interaction. What sets our solution apart are its unique features, tailored specifically for the Indian Government. The integration of sentiment analysis, issue tracking, and departmental categorization is complemented by an intuitive interface, a minimal tech stack, and real-time insights, empowering swift crisis response and evidence-based decision-making.
Keywords: AI-driven feedback system, Web scraping, Sentiment analysis, Real-time media monitoring, Crisis management, Government communication, Machine learning, Departmental feedback.
|
DOI:
10.17148/IJARCCE.2024.134222
