About Lamu News
AI-powered news analysis for a more informed world. We help readers see past the headline and understand how news is framed.
🎯 Our Mission
In an era of information overload, understanding how a story is told matters as much as what the story says. Lamu News was built to give every reader the analytical tools traditionally reserved for media researchers and political scientists.
We believe that transparency in media framing empowers better-informed citizens. Our platform automatically collects articles from dozens of major news publishers, runs each one through rigorous AI analysis, and presents the results in a clear, accessible format — all completely free.
💡 Our Core Belief
No news source is perfectly neutral. By surfacing framing patterns, sentiment, and loaded language, we help readers recognize these patterns and form their own informed opinions rather than absorbing narratives uncritically.
⚙️ How It Works
Our automated pipeline runs 24/7, ingesting and analyzing articles from across the political spectrum. Here's the process:
We monitor RSS feeds from 49+ major news publishers to discover new stories as they break.
Each article is fetched, cleaned, and stripped of ads, navigation, and boilerplate to isolate the pure article text.
AI models evaluate the article for sentiment, political framing, loaded language, and bias indicators.
Results are stored and displayed alongside the original article with clear, visual breakdowns.
🔍 What We Analyze
Every article goes through a multi-dimensional analysis. Here's what we measure:
Measures the emotional tone of the writing — from highly negative to highly positive. Factual reporting tends to sit near 0.
AI-estimated percentages for Left, Center, and Right framing. The derived Bias Score is calculated as (Right% − Left%) / 100.
Identifies emotionally charged, persuasive, or misleading terms used in the article that may influence reader perception.
How confident the AI model is in its own assessment. Lower confidence means more ambiguity in the source material.
A concise, neutrally-worded summary of the article stripped of editorial framing and loaded language.
📰 Our Sources
We currently monitor 49+ major news publishers spanning the full political spectrum. Sources are selected to represent a broad range of editorial perspectives, including:
…and many more. New sources are added regularly. All sources are stored in our database and can be activated or deactivated independently.
⚖️Transparency & Limitations
We believe in full transparency about our methods and their inherent limitations:
⚠️ AI-Estimated, Not Objective Truth
All bias and sentiment scores are AI-estimated assessments of linguistic patterns. They are computational evaluations, not definitive political classifications. We encourage readers to read the original sources directly.
🤖 Model Limitations
AI language models can reflect biases present in their training data. Our confidence scores help indicate when the model is less certain about its assessment. Low-confidence results should be interpreted with additional caution.
🔄 Continuous Improvement
We regularly refine our analysis prompts, update our source list, and adjust our pipeline to improve accuracy. The platform is under active development and gets better with every iteration.
👥 The Team
Lamu News is an independent project built by a small team passionate about media literacy and AI transparency. We are developers, designers, and data enthusiasts who believe technology should serve the public interest.
We're not affiliated with any political party, media organization, or advocacy group. Our only agenda is making the news ecosystem more transparent for everyday readers.
✉️ Get in Touch
Have questions, feedback, or partnership inquiries? We'd love to hear from you.