Round 1 Winners!
Proof of Usefulness Report

Art Chang

Analysis completed on 3/17/2026

-9.9
Proof of Usefulness Score
Lab Mode

The submission is characterized by highly exaggerated and unsupported claims, such as stating 'most people have used my product' and claiming an unverifiable team size of 125. The core project appears to merely reference a published academic paper on machine learning rather than a functioning B2B or consumer product, making the asserted audience reach of 'everyone' and market cap of 2,500,000 highly dubious. Due to the complete lack of verifiable traction, vague technical descriptions, and numerous red flags, the quality multipliers are reduced and the project receives a negative evaluation score.

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Score Breakdown

Real World Utility+2.5
Audience Reach Impact-5.0
Technical Innovation+3.0
Evidence Of Traction-10.0
Market Timing Relevance+1.0
Functional Completeness-0.5
Subtotal-9
Usefulness Multiplierx1.1
Final Score-10

Project Details

Project URL
Description
..., "Detecting Asian Values in Asian News via Machine Learning Text Classification," appears in Springer Nature's 2021 book "Advances in Data Science and Information...

Algorithm Insights

Market Position
Early stage requiring focused development
User Engagement
Documented reach suggests active user community
Technical Stack
Modern tech stack aligned with sponsor technologies

Recommendations to Increase Usefulness Score

Document User Growth

Provide specific metrics on user acquisition and retention rates

Showcase Revenue Model

Detail sustainable monetization strategy and current revenue streams

Expand Evidence Base

Include testimonials, case studies, and third-party validation

Technical Roadmap

Share development milestones and feature completion timeline