Oneida Silverware Set, Camlynn Everyday Flatware 4-Piece Salad Forks Set, Service For 4, 18/0 Stainless Steel, Mirror Finish, Dishwasher Safe, Home And Kitchen Utensils (Silver, 4 Piece)

Oneida Silverware Set, Camlynn Everyday Flatware 4-Piece Salad Forks Set, Service For 4, 18/0 Stainless Steel, Mirror Finish, Dishwasher Safe, Home And Kitchen Utensils (Silver, 4 Piece)

ASIN: B001EY6CFS
Analysis Date: Oct 30, 2025 (re-analyzed Oct 30, 2025)

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Review Analysis Results

B
Authenticity Grade
18.00%
Fake Reviews
4.54
Original Rating
4.10
Adjusted Rating

Analysis Summary

The review set shows mostly authentic characteristics with some minor concerns. Positive aspects include: natural rating distribution (12 five-star, 1 four-star, 1 three-star, 1 two-star), detailed personal stories with specific timelines (55th anniversary, decade-old purchases), and varied writing styles. Concerns include: high verification rate (all reviews marked 'V'), some repetitive praise language about quality/weight, and a few reviews with slightly generic phrasing. The mix of critical reviews (sizing complaints, mismatch issues) adds credibility. Overall pattern suggests legitimate product with enthusiastic customers rather than systematic fakery.

Review Statistics

1,586
Total Reviews on Amazon
-0.44
Rating Difference

Price Analysis

Price analysis pending

Price insights will be available shortly.

Understanding This Analysis

What does Grade B mean?

This product has good review authenticity with minor concerns. While most reviews appear genuine, we detected some patterns that warrant mild caution.

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 (4.54 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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