Multi-Source Newspaper Summarization and Comparison System

In today’s digital era, news is reported simultaneously by multiple media outlets, often presenting the same event with varying levels of detail, emphasis, and perspective. For readers, this abundance of information can be overwhelming and time- consuming to analyze. This paper presents a Multi-Source Newspaper Summarization and Comparison System designed to automatically collect news articles from different sources, generate concise summaries, and compare reporting patterns across newspapers. The proposed system applies natural language processing techniques to preprocess text, extract important content, and measure similarity between articles. By presenting a unified and comparative view of news coverage, the system helps readers quickly understand key facts while identifying overlaps and differences in reporting. The design emphasizes simplicity, interpretability, and practical usability, making it suitable for academic and real-world applications.