Lee Women's Ultra Lux Comfort with Flex Motion Straight Leg Jean
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Review Analysis Results
Analysis Summary
The review set shows a moderately suspicious profile with several concerning patterns balanced against legitimate-looking reviews. Key findings: 1) Extremely high positive bias with 10/15 reviews at 5★ (67%) and only 3 negative reviews, creating an unnatural distribution; 2) Multiple reviews use nearly identical phrasing about 'perfect fit' and 'comfortable' with minimal product detail; 3) Several reviews appear formulaic with repetitive structure focusing on fit, comfort, and quality in the same order; 4) However, the presence of authentic-seeming negative reviews (including detailed fit complaints and language barriers) and specific usage scenarios (animal shelter work, horse riding) provides credibility. The mix of detailed personal experiences with some generic positive reviews suggests a combination of genuine customers and potentially incentivized or low-effort reviews.
Review Statistics
About Review Data Collection
We extract as much review data as Amazon makes available at the time of analysis. The amount may vary due to Amazon's rate limiting, regional restrictions, or other factors. Our analysis is based on the reviews we successfully collected.
Want to analyze more reviews? Install the Null Fake Chrome extension to capture and analyze additional reviews as you browse Amazon.
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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 (3.40 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 (4.00 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.
