16 Piece Dinner Forks Set, Food Grade Extra-Fine Stainless Steel Dessert Salad Forks Silverware, Metal Forks for Home Kitchen Restaurant Hotel, 8 Inches, Mirror Finish & Dishwasher Safe

16 Piece Dinner Forks Set, Food Grade Extra-Fine Stainless Steel Dessert Salad Forks Silverware, Metal Forks for Home Kitchen Restaurant Hotel, 8 Inches, Mirror Finish & Dishwasher Safe

ASIN: B08CRKHCPB
Analysis Date: Oct 30, 2025 (re-analyzed Oct 30, 2025)

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Review Analysis Results

C
Authenticity Grade
25.00%
Fake Reviews
4.67
Original Rating
4.10
Adjusted Rating

Analysis Summary

The review set shows mixed authenticity signals. Positive indicators include: natural variation in review length and style, some critical reviews (3-star), and generally plausible content about silverware quality and missing fork problems. However, concerning patterns include: high proportion of verified purchases (100%), overwhelmingly positive ratings (7/9 are 5-star), and several reviews with generic, repetitive praise about 'sturdy,' 'good quality,' and 'excellent price.' The Spanish review (#9) appears authentic but stands out in an otherwise English-only set. The moderate fake percentage reflects that while many reviews seem genuine, the high verification rate combined with repetitive positive language suggests some potential manipulation.

Review Statistics

2,997
Total Reviews on Amazon
-0.57
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 (4.10 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 (4.67 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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