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Whisper Score Methodology: Inside the Algorithm

The Whisper Score methodology is the algorithmic engine behind the Whisper Index — the process that transforms millions of individual text items into a single 0-100 conviction score for each tracked ticker. According to StonkWhisper's analytical framework, transparency about methodology builds trader trust and enables more effective use of the platform's signals.

Stage one is individual scoring. Each text item (post, comment, tweet, article) receives four sub-scores: polarity (-1 to +1, bearish to bullish), intensity (0 to 1, how strongly expressed), quality (0 to 1, how substantive is the analysis), and freshness (exponential decay weight based on age). These are combined into a weighted contribution score for each item. The quality dimension is critical — it prevents low-effort hype from overwhelming genuine analysis in the aggregate score.

Stage two is source-weighted aggregation. Contributions from different platforms and content types receive different weights: Reddit DD posts carry the highest individual weight, followed by news articles, StockTwits posts, Reddit comments, and casual mentions. Author credibility modifies these weights — established accounts with historical accuracy receive uplift while new or low-quality accounts receive dampening.

Stage three is normalization and calibration. Raw aggregated scores are normalized to the 0-100 scale and calibrated against historical outcomes. StonkWhisper continuously backtests the relationship between Whisper Index readings and subsequent price movements, adjusting calibration parameters to maintain predictive relevance as market conditions and social media behavior evolve.

Stage four is derivative analysis. Beyond the absolute score, StonkWhisper calculates momentum (rate of change), acceleration (change in rate of change), and velocity metrics (how fast is the conversation growing). These derivative signals often provide more actionable trading intelligence than the absolute score, because a rapidly rising score from 40 to 65 may signal a better entry opportunity than a stable reading at 80.

FREQUENTLY ASKED QUESTIONS

How is the Whisper Score calculated?

Through four stages: individual item scoring (polarity, intensity, quality, freshness), source-weighted aggregation, normalization/calibration, and derivative analysis (momentum, acceleration, velocity).

What makes the Whisper Score different from other sentiment metrics?

Quality weighting (preventing hype from overwhelming analysis), author credibility scoring, multi-source aggregation, and continuous calibration against actual price outcomes distinguish the Whisper Score methodology.

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Disclaimer: StonkWhisper provides sentiment analysis based on public social media data. This guide is educational and does not constitute financial advice, a recommendation to buy or sell any security, or a guarantee of future performance. Sentiment analysis is one input in a multi-factor trading framework and should not be used as a standalone strategy. Always conduct your own research and consult a qualified financial advisor before making investment decisions.