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2 starsPython

Wikimetron – Surface hidden sensitivity and risk in Wikipedia

by hjbarraza·Mar 12, 2026·2 points·0 comments
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AI Analysis

●●SolidNiche GemBig Brain

Aggregates 27 signals like sockpuppets and revert risk into a single trust score.

Strengths
  • •Metrics like sockpuppet detection and revert risk signal genuine depth.
  • •Modular pipeline allows easy addition of new risk signals over time.
  • •Direct API integration avoids scraping maintenance and rate limit headaches.
Weaknesses
  • •README is in French, limiting immediate adoption by English-speaking developers.
  • •Competes with ORES models without clear benchmark comparison data provided.
Category
Data
Target Audience

Researchers, journalists, and fact-checkers citing Wikipedia

Similar To

ORES · WikiTrust · WikiQuality

Post Description

Score any Wikipedia page for sensitivity, quality, and risk in seconds.

Wikimetron analyzes Wikipedia pages across multiple dimensions — editorial quality, content sensitivity, and informational risk — by pulling data directly from the Wikimedia API. It evaluates things like source density, edit frequency, controversy signals, and structural completeness to generate composite scores that would take a human reviewer hours to assess manually.

Built for researchers, journalists, and anyone who needs to know how much to trust a Wikipedia page before citing it.

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