Transparency
How We Measure
Media Bias
Daily Composite uses a multi-model AI consensus approach — four of the world's most advanced language models independently score every article, then we average the results to produce a single, defensible bias signal.
The Scale
A 1–5 Spectrum
Scores reflect framing and presentation, not factual accuracy. A score of 3 does not mean an article is correct — it means its presentation is balanced. A score of 1 or 5 means the language and framing skew strongly toward one end of the political spectrum.
The Panel
Four Independent Judges
No model sees another's score before submitting. Independence is the point — it hedges against any single model's blind spots or training-data biases.
Claude
claude-sonnet-4
GPT-4o
gpt-4o
Gemini
gemini-2.0-flash
Grok
grok-3-mini
Final score = average of all four models → (Claude + GPT + Gemini + Grok) ÷ 4
The Rubric
Five Bias Signals
Word choice
Emotive vs. neutral language; loaded or charged terms
Framing
What is emphasized, what is buried or omitted
Sources cited
Which voices are amplified, which are absent
Perspective prominence
Whose viewpoint leads or anchors the story
Emotional language
Fear, outrage, celebration, or alarm cues
Each model receives the full article text and evaluates all five signals simultaneously before returning a single 1–5 score.
The Pipeline
From Source to Score
Ingest
RSS feeds from 40+ sources across the political spectrum are pulled every 30 minutes.
Queue
New articles are deduplicated and queued for bias analysis within minutes of ingestion.
Analyze
Four AI models independently read each article and return a 1–5 bias score with reasoning.
Consensus
Scores are averaged into a single consensus score and stored alongside the article.
Publish
Articles appear on site with their score, color-coded by lean, updated in real time.
Limitations
What We Don't Measure
✗ Factual Accuracy
We score framing, not facts. A biased article can be factually correct. We do not fact-check.
✗ Malicious Intent
A score reflects how an article reads — not why the author wrote it that way.
✗ Full Article Text
We analyze headlines and available descriptions. Paywalled full text may not be available.
Privacy
Your Data Stays Private
When you use the Bias Checker tool, article text is sent to AI APIs for analysis and immediately discarded. We store only the numerical scores and a short hash for shareable links. We never store full article text.
FAQ
Frequently Asked Questions
How is media bias measured?
Daily Composite measures media bias using four large language models that independently analyze each article for word choice, framing, sources cited, prominence of perspectives, and emotional language. The four scores are averaged into a consensus.
What AI models detect bias?
We use Claude (Anthropic), GPT-4o (OpenAI), Gemini 2.0 Flash (Google), and Grok-3 Mini (xAI). Each model scores independently — no model sees another's result until after scoring.
Is AI bias analysis accurate?
AI bias analysis captures linguistic and framing patterns but is not infallible. Using four independent models and averaging results reduces single-model blind spots and provides a more robust signal than any single algorithm.
Does a bias score mean the article is wrong?
No. Bias scoring reflects framing and presentation, not factual accuracy. A factually accurate article can still lean left or right in how it frames information. Daily Composite does not fact-check articles.
Can I check any article?
Yes. Use the Bias Checker tool on our homepage to analyze any URL or pasted text. Results are returned in seconds and include a shareable link.
What happens to article text I submit?
Article text is sent to AI APIs for analysis and immediately discarded. We store only the numerical scores and a short hash for shareable links. We never store full article text.
See it in action
Paste any article URL and get a bias score in seconds.