Utopia Bedding Queen Fitted Sheet - Bottom Sheet - Deep Pocket - Soft Microfiber - Shrinkage and Fade Resistant - Easy Care -1 Fitted Sheet Only (White)

Utopia Bedding Queen Fitted Sheet - Bottom Sheet - Deep Pocket - Soft Microfiber - Shrinkage and Fade Resistant - Easy Care -1 Fitted Sheet Only (White)

ASIN: B00XK9CO16
Analysis Date: Nov 2, 2025 (re-analyzed Nov 2, 2025)

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Review Analysis Results

D
Authenticity Grade
42.00%
Fake Reviews
4.73
Original Rating
3.70
Adjusted Rating

Analysis Summary

The review set shows moderate signs of inauthenticity with several concerning patterns. While there are some legitimate-sounding reviews with specific details and balanced feedback, multiple red flags emerge: 1) Extremely high 5-star concentration (12/15 reviews are 5-star, 80%) with repetitive positive phrasing, 2) Multiple reviews using nearly identical language about 'soft material,' 'deep pockets,' and 'perfect fit' suggesting coordinated content, 3) One review (R36OK9VO05QLM1) appears duplicated verbatim, 4) Several reviews are overly generic with minimal substance ('soft. comfortable. great quality'), 5) Unusual that 14/15 reviews are verified purchases. The presence of a few 3-4 star reviews with more nuanced feedback provides some balance, but the overall pattern suggests potential review manipulation.

Review Statistics

118,142
Total Reviews on Amazon
-1.03
Rating Difference

Price Analysis

Price analysis pending

Price insights will be available shortly.

Understanding This Analysis

What does Grade D mean?

This product has significant review authenticity issues. Many reviews show patterns consistent with fake or incentivized reviews. Exercise caution.

Adjusted Rating Explained

The adjusted rating (3.70 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 (4.73 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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