Replacement Filter Fit for LG Microwave Filter 5230W1A003A JVM7195SK6SS LMV1650ST, LMV1650SW, LMV2031BD, LMV2031SB,LMVM2085SB, LMVH1711ST, LMV2031ST Charcoal Filte-r (Pack of 1)

Replacement Filter Fit for LG Microwave Filter 5230W1A003A JVM7195SK6SS LMV1650ST, LMV1650SW, LMV2031BD, LMV2031SB,LMVM2085SB, LMVH1711ST, LMV2031ST Charcoal Filte-r (Pack of 1)

ASIN: B0C9964NPS
Analysis Date: Oct 25, 2025

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Review Analysis Results

C
Authenticity Grade
28.00%
Fake Reviews
4.89
Original Rating
4.20
Adjusted Rating

Analysis Summary

This product shows moderate signs of review manipulation with several concerning patterns. The review set has an extremely high 5-star concentration (8 out of 9 reviews are 5-star, 89%), which is statistically unusual for most products. Multiple reviews exhibit generic, repetitive language with minimal detail ('Works great', 'Fit perfectly', 'Work's well'). Several reviews lack verification badges despite claiming to be verified, suggesting potential manipulation of the verification system. However, there are some legitimate-seeming reviews with specific details about LG microwave compatibility and aftermarket part comparisons that provide balance. The overall pattern suggests some artificial boosting but not overwhelmingly so.

Review Statistics

229
Total Reviews on Amazon
-0.69
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 (4.20 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 (4.89 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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