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Development of an AI-Powered Global News Bias and Narrative Intelligence System for Real-Time News Analysis
Subject area: Science,Engineering and Technology · Area of research: AI, NLP for News Analysis
DOI: https://doi.org/10.64388/IREV9I9-1715507
Abstract
The rapid growth of digital news platforms and the rise of AI-generated misinformation have increased the need for intelligent systems that help users critically evaluate news content. Many existing news websites simply display headlines and articles without providing tools to analyze bias, verify facts, or understand different narratives, making it difficult for readers to judge the credibility of information. This project proposes an AI-Powered Global News Bias and Narrative Intelligence Platform that transforms traditional news reading into an analytical and interactive experience. The system is developed as a full-stack web application using React and TypeScript for the frontend and Node.js with Express for the backend, integrated with a Supabase PostgreSQL database for efficient data management. The platform retrieves live news articles from multiple APIs and applies artificial intelligence techniques such as news summarization, bias detection, narrative analysis, fact checking, and cross-language comparison to provide deeper insights into news content. In addition to analysis features, the system includes functionalities such as an AI chatbot for user interaction, automated newsletters, video search, personalized dashboards, and audio news briefings. It notifications based on user interests to enhance the overall user experience. Experimental testing with real-time news data shows that the platform can efficiently collect, process, and analyze news articles while delivering AI-generated insights quickly. The proposed system helps users better understand current events by providing contextual analysis and intelligent recommendations.
Keywords
News Intelligence Platform, Bias Detection, Narrative Analysis, Fake News Detection, AI Chatbot, News Aggregation, React, Node.js, Supabase.
References
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How to cite this paper
@article{1715507,
author = {V. Nagendran, Dr. S. Parthasarathy},
title = {Development of an AI-Powered Global News Bias and Narrative Intelligence System for Real-Time News Analysis},
journal = {Iconic Research And Engineering Journals},
year = {2026},
volume = {9},
number = {9},
pages = {2626-2632},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1715507.pdf},
abstract = {The rapid growth of digital news platforms and the rise of AI-generated misinformation have increased the need for intelligent systems that help users critically evaluate news content. Many existing news websites simply display headlines and articles without providing tools to analyze bias, verify facts, or understand different narratives, making it difficult for readers to judge the credibility of information. This project proposes an AI-Powered Global News Bias and Narrative Intelligence Platform that transforms traditional news reading into an analytical and interactive experience. The system is developed as a full-stack web application using React and TypeScript for the frontend and Node.js with Express for the backend, integrated with a Supabase PostgreSQL database for efficient data management. The platform retrieves live news articles from multiple APIs and applies artificial intelligence techniques such as news summarization, bias detection, narrative analysis, fact checking, and cross-language comparison to provide deeper insights into news content. In addition to analysis features, the system includes functionalities such as an AI chatbot for user interaction, automated newsletters, video search, personalized dashboards, and audio news briefings. It notifications based on user interests to enhance the overall user experience. Experimental testing with real-time news data shows that the platform can efficiently collect, process, and analyze news articles while delivering AI-generated insights quickly. The proposed system helps users better understand current events by providing contextual analysis and intelligent recommendations.},
keywords = {News Intelligence Platform, Bias Detection, Narrative Analysis, Fake News Detection, AI Chatbot, News Aggregation, React, Node.js, Supabase.},
month = {March},
doi = {https://doi.org/10.64388/IREV9I9-1715507}
}