Oneida Savor Everyday Flatware Dinner Forks, Set of 6, 18/0 Stainless Steel, Silverware Set, Dishwasher Safe

Oneida Savor Everyday Flatware Dinner Forks, Set of 6, 18/0 Stainless Steel, Silverware Set, Dishwasher Safe

ASIN: B00XDS13C0
Analysis Date: Oct 30, 2025 (re-analyzed Oct 30, 2025)

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Review Analysis Results

C
Authenticity Grade
28.00%
Fake Reviews
4.47
Original Rating
3.80
Adjusted Rating

Analysis Summary

The review set shows mixed authenticity signals. Positive indicators include: natural variation in ratings (5★=13, 4★=2, 3★=1, 1★=1), detailed negative reviews with specific measurements and comparisons, and varied review lengths with some containing specific usage scenarios. Concerning patterns include: high concentration of 5-star reviews (76%), repetitive language about 'weight/heft' and 'matching existing sets' across multiple reviews, and several brief, generic positive reviews that lack substantive detail. The presence of legitimate-sounding critical reviews (particularly the detailed 1-star review with measurements and the 3-star review about manufacturing defects) suggests some organic review activity, but the overwhelming positivity ratio and repetitive phrasing in the 5-star reviews indicate potential review manipulation.

Review Statistics

1,067
Total Reviews on Amazon
-0.67
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 (3.80 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 (4.47 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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