Independent methodology for detecting fake reviews and influencer manipulation in Thailand restaurant rankings.
Trust Score Formula
- Rating (50%): Google star rating / 5 × 50. A 4.5★ restaurant contributes 45 points.
- Volume (40%): log10(reviews) × 12, capped at 40. Volume matters, but diminishing returns — 1,000 reviews isn't 10× better than 100.
- Local Guide Ratio (10%): % of scraped reviewers who are Google Local Guides × 20, capped at 10. Local Guides are Google-verified high-volume reviewers — hard to fake at scale.
- Author Authority (5%): log10(avg reviews per author) × 2, capped at 5. Reviewers who've written many reviews are harder to astroturf.
Why We Built This
Bangkok and Pattaya have a massive influencer-driven restaurant marketing ecosystem. A restaurant can get 50,000 Instagram views, 500 TikTok reposts, and a wave of follower visits — generating hundreds of 5-star reviews from people who came because of the influencer, not because the food is great.
The result is restaurant rankings that reflect marketing budgets, not food quality. Thaigle fixes this by using data signals that influencer campaigns cannot easily fake: Local Guide ratios, reviewer authority, and volume-adjusted scoring.
FAQ
We measure the ratio of Google Local Guide reviewers — verified high-volume reviewers given status by Google itself. A restaurant with 90%+ Local Guide reviewers is extremely difficult to fake-review at scale. We combine this with review volume (log-scaled) and reviewer authority (average reviews per author) to build a composite Trust Score.
Trust Score (0-100) = rating contribution (50%, weighted by Google star rating) + volume contribution (40%, log10 scaled — 10 reviews adds less than 10x the next 10) + Local Guide ratio (10%, max at 50%+ Local Guides) + reviewer authority (5%, log-scaled average reviews per author). A score of 80+ means the rating is statistically trustworthy.
No. Trust Score is derived entirely from public Google Maps data — ratings, review counts, reviewer types. Thaigle does not edit, inflate, or accept payment to modify any organic listing's Trust Score.
Influencer manipulation occurs when a restaurant's online reputation is driven by paid social media posts (Instagram, TikTok, YouTube) that generate visits from followers who leave reviews out of brand loyalty rather than actual food quality. The result: high star ratings from low-credibility reviewers. Our Local Guide ratio catches this — influencer-driven restaurants show low Local Guide ratios despite high review counts.
The master database rebuilds continuously. Restaurant listings, ratings, and review counts refresh from Google Maps every 24 hours. The website redeploys automatically on data change.
ℹ️How we rank places▾
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