Jin Office Monitor Stand Heavy Duty for 13"-49" Inch Monitor | Strongest Gas Spring Arm with 22KG Wt. Cap| Check VESA Holes Behind Your Monitor 100x100, 200x200 VESA (Clamp/Drill Installation)

Jin Office Monitor Stand Heavy Duty for 13"-49" Inch Monitor | Strongest Gas Spring Arm with 22KG Wt. Cap| Check VESA Holes Behind Your Monitor 100x100, 200x200 VESA (Clamp/Drill Installation)

ASIN: B0CKW835X3
Analysis Date: Sep 15, 2025 (re-analyzed Sep 15, 2025)

Review Analysis Results

B
Authenticity Grade
18.00%
Fake Reviews
4.80
Original Rating
4.40
Adjusted Rating

Analysis Summary

The reviews show generally authentic characteristics with a low fake percentage. Most reviews contain specific details about monitor models (Samsung M7 43", LG 49WQ95C, AW3223DWF), installation experiences, and practical usage observations. The 5-star rating dominance (19/21 reviews) is typical for well-reviewed monitor accessories. However, some minor concerns include: 1) Two reviews (R28VKA1SZYWJC6 and R1BFJAN3CLIBKQ) appear duplicated with slight variations, 2) Some reviews use slightly promotional language ('game-changer', 'worth every penny'), and 3) One review (R10394PKCRMQWE) mentions proactive customer service calls which could be exaggerated. The presence of a legitimate 2-star negative review (R1GZK7RTVC5UZM) about VESA mount compatibility issues adds credibility to the overall authenticity.

Review Statistics

72
Total Reviews on Amazon
-0.40
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 (4.40 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 (4.80 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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