Original Summary

I've been working on a side project called NewsLens for the past few months. The idea came from something that annoyed me about following the news: one real-world event might produce dozens of articles across different outlets, but most news sites still present them as completely separate pieces of content. It makes it hard to understand what the actual underlying stories are, how they're developing, and how different sources are covering them. So I built NewsLens around stories rather than articles . It currently pulls articles from 20+ news sources and automatically groups related coverage into evolving stories. The main interface is a story map where you can explore those stories rather than scroll through another chronological news feed. I also added: tracking of how stories develop over time sentiment and other NLP analysis across coverage links back to the underlying articles a Q&A system that searches the collected reporting and gives citation-backed answers There's quite a bit going on behind the scenes too. The whole pipeline runs automatically, from fetching and processing articles to embeddings, story detection, database updates and deployment. I built most of it with Python, PostgreSQL/pgvector, FastAPI, Azure and Vercel. NewsLens: [ https://newslens-ashy.vercel.app/]() It's very much still a work in progress, and this is the first time I'm deliberately putting it in front of people I don't know. I'd especially like feedback on: Is it obvious what the site is for when you first open it? Is the story map actually useful, or does it just look interesting? What would make you come back and use something like this regularly? Also completely open to hearing what feels confusing, unnecessary, or broken. That's probably more useful to me right now than compliments.   submitted by   /u/Ok_Ad_182 [link]   [comments]

  • 情报分类：商业与市场研究
  • 分类依据：内容涉及商业、投资或市场动态
  • 信息来源：Reddit · SideProject
  • 发布时间：2026/9/14 07:15:03