1,000 Plastic Disposable Forks Bulk Black Medium Weight Disposable Silverware Plastic Cutlery Fork

1,000 Plastic Disposable Forks Bulk Black Medium Weight Disposable Silverware Plastic Cutlery Fork

ASIN: B0B489LSCY
Analysis Date: Oct 30, 2025 (re-analyzed Oct 30, 2025)

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Review Analysis Results

C
Authenticity Grade
28.00%
Fake Reviews
3.31
Original Rating
2.80
Adjusted Rating

Analysis Summary

The review set shows mixed authenticity signals. Positive aspects include natural language variation across reviews, specific product complaints about flimsiness that appear genuine, and international language diversity (French, Spanish). However, concerning patterns include: 1) Extreme polarization with 5-star reviews using generic praise ('good product', 'good for office') while 1-2 star reviews provide detailed mechanical failure descriptions, 2) Several 5-star reviews lack product specifics and read like template responses, 3) The 'V' verification badge appears on all reviews which is statistically unusual for authentic review distribution. The moderate fake percentage reflects that while some reviews appear fabricated for positive promotion, many negative reviews show authentic user experiences with consistent complaints about structural weakness.

Review Statistics

392
Total Reviews on Amazon
-0.51
Rating Difference

Price Analysis

Price analysis pending

Price insights will be available shortly.

Understanding This Analysis

What does Grade C mean?

This product has moderate review authenticity concerns. A notable portion of reviews show suspicious patterns. Consider reading reviews carefully before purchasing.

Adjusted Rating Explained

The adjusted rating (2.80 stars) represents what we estimate this product's rating would be if fake reviews were removed. This product's adjusted rating is lower than Amazon's displayed rating (3.31 stars), suggesting positive fake reviews may be inflating the score.

How We Detect Fake Reviews

Our AI analyzes multiple factors: language patterns (generic vs. specific), reviewer behavior (history, timing), temporal anomalies (review clusters), verification status, sentiment authenticity, and statistical outliers. No single factor determines a review is fake - we look at the combination of signals.

Important Limitations

No automated system is perfect. Sophisticated fake reviews can evade detection, and some genuine reviews may be incorrectly flagged. Use this analysis as one data point in your purchasing decision, not the only factor. Reading actual review content yourself is always valuable.

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