Yaomiao 16 Pcs Thanksgiving Table Decor Pumpkin Place Card Holders Mini Name Number Holders for Thanksgiving Table Setting Fall Autumn Party Photo Picture Wedding Decor(Green)

Yaomiao 16 Pcs Thanksgiving Table Decor Pumpkin Place Card Holders Mini Name Number Holders for Thanksgiving Table Setting Fall Autumn Party Photo Picture Wedding Decor(Green)

ASIN: B0D3V34GRB
Analysis Date: Nov 7, 2025

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Review Analysis Results

C
Authenticity Grade
28.00%
Fake Reviews
3.80
Original Rating
3.30
Adjusted Rating

Analysis Summary

The review set shows moderate authenticity concerns primarily due to duplicate reviews and suspicious rating patterns. Two reviews (R130NWUV1UQIWH and R3D09NQ4ZTS69T) appear verbatim twice, which is highly unusual for genuine reviews. The rating distribution is polarized with 5-star reviews (50%) and negative reviews (33%), with minimal middle-ground ratings. However, the presence of detailed negative reviews mentioning specific product issues (broken stems, packaging problems) lends credibility, and the verified purchase rate is relatively high at 67%. The duplicate content is the most significant red flag, but the overall pattern suggests a mix of genuine and potentially manipulated reviews.

Review Statistics

27
Total Reviews on Amazon
-0.50
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 (3.30 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 (3.80 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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