Replacement Filter 5230W1A003A Microwave Charcoal Filter Replacement for LG Microwave Air Filter LMV2031ST, LMVH1750SB, LMV2031SS, LMVH1750ST, LMV2031BD, LMV1650ST, LMVH1750SW, LMV2031SB, LMHM2237BD

Replacement Filter 5230W1A003A Microwave Charcoal Filter Replacement for LG Microwave Air Filter LMV2031ST, LMVH1750SB, LMV2031SS, LMVH1750ST, LMV2031BD, LMV1650ST, LMVH1750SW, LMV2031SB, LMHM2237BD

ASIN: B0DPX6B993
Analysis Date: Oct 25, 2025 (re-analyzed Oct 25, 2025)

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Review Analysis Results

C
Authenticity Grade
28.00%
Fake Reviews
3.73
Original Rating
3.20
Adjusted Rating

Analysis Summary

The reviews show a mixed pattern with some legitimate characteristics and a few concerning elements. Positive aspects include: specific model references (LMHM2237ST, LG 'Extend a Vent'), detailed installation experiences, and consistent complaints about the product's fragility which aligns with the nature of a plastic microwave vent cover. However, concerns include: multiple duplicate reviews (RIX25TCH81FB appears twice with identical content), some overly generic 5-star reviews lacking detail, and a suspicious pattern where several reviews mention breaking within months but still give high ratings. The rating distribution (mostly 5-star with some 1-2 star reviews) suggests some authentic negative experiences, but the duplicate content and generic positive reviews indicate some manipulation.

Review Statistics

333
Total Reviews on Amazon
-0.53
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 (3.20 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 (3.73 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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