Engagement ratios need context
Subscriber counts alone are weak evidence. The model emphasizes median views, likes, and comments per view.
Market signal integrity assessment
Market Signal Integrity Score
A fixed scoring model for evaluating whether public social engagement may be creating artificial product demand or investor-facing market signal risk.
Fixed model output
39/100
Score is computed from measured evidence fields and fixed model weights. Viewers do not tune the model.
Traffic bursts are weighted separately
Sharp view spikes can be normal after ads, launches, or press. They become stronger evidence when paired with shallow engagement.
Comment relevance is a core signal
Uniformly positive chains, generic praise with high likes, repeated price anchoring, and stock-focused remarks are stronger manipulation signals than raw comment volume.
Only collected fields are scored
Uncollected signals are omitted from the page instead of being shown as zero-value inputs or inferred evidence.
Language templates are detectable
Repeated adjectives, identical purchase intent, shallow specificity, and unnatural punctuation can be scored across every channel video.
This site presents a fixed market-signal risk model. It does not assert that Ubiquiti or any other channel committed fraud. Definitive conclusions require authenticated analytics, source traffic, account metadata, and reproducible sampling.
Market signal risk
Channel
Insufficient data
0
/ 100
Evidence Examples
Why Regulators Care
Signal Breakdown
Method
This is a probabilistic risk model, not a definitive fraud claim. It scores mismatches between audience size, engagement depth, comment quality, sentiment saturation, price anchoring, low-specificity language, and unusually high likes on sampled comments. This version uses only the public Ubiquiti scrape. Fields not collected in the public scrape are omitted from the displayed score. Strong conclusions require raw YouTube Analytics, comment account metadata, referral sources, stock-symbol comment sampling, cross-video account reuse analysis, and repeatable sampling.