How HypeMetrix Calculates Scores

HypeMetrix aggregates opinions from multiple sources, analyzes sentiment with AI, and blends everything into a single, transparent score.

Data Sources

We pull from three distinct source types to capture the full spectrum of user and expert opinion.

  • Reddit

    Real user discussions, complaints, and praise from enthusiast communities.

  • YouTube

    Detailed video reviews from creators and tech channels.

  • Editorial

    Written reviews and articles from tech publications and blogs.

The Scoring Pipeline

For each source, we score individual criteria (sound, comfort, battery, build, etc.) on a 0–100 scale. Each criterion is weighted by its importance for that product type.

We calculate a per-source overall score. If a source misses some criteria, we normalize the result so the product isn't unfairly penalized.

Finally, we blend per-source scores using global source weights and a confidence multiplier. Sources with limited data contribute less; unavailable sources are excluded entirely.

Formula Summary

sourceScore = sum(criterionScore × criterionWeight) / totalWeightFound

blendedScore = sum(sourceScore × sourceWeight × confidence) / sum(sourceWeight × confidence)

  • Reddit weight: 45%
  • Editorial weight: 35%
  • YouTube weight: 20%

Confidence Levels

Data quality affects how much a source contributes to the final score.

  • High

    All major sources had sufficient data for a reliable analysis.

  • Medium

    At least one source had limited data. Results may vary slightly.

  • Low

    Most sources had limited or no data. Treat scores with caution.

Limitations & Transparency

Our scores reflect aggregated public opinion at a point in time. They are not a substitute for hands-on testing, and source availability can vary by product and language.