How we measure this.
Our core product is a live read on what the market’s crowd is saying. We stream public discussion from finance communities, find the companies and assets being talked about, score the tone with a financial language model, and roll it into figures that always show the sample behind them. Every number here names its source, and where a source isn’t ours, we say so.
The pipeline
Reddit → clean → extract → score → roll upStream the social tape
We stream posts and comments from a fixed set of finance subreddits — r/wallstreetbets, r/stocks, r/investing, r/options, r/ETFs and r/commodities — capturing each with its timestamp, author and score.
Strip the noise
Bot templates, quoted replies and boilerplate are removed before anything is measured, so automated and copy-paste content cannot inflate a reading.
Find the entities
A named-entity recogniser, paired with a cashtag parser and a curated reference dictionary, pulls tickers, company names, ETFs, commodities and macro indicators out of raw text. Each extraction carries a confidence score built from several signals — how it was matched, the surrounding financial context, whether it is a known ambiguous word — and only mentions above a threshold are counted.
Read the sentiment
FinBERT classifies every surviving mention as positive, neutral or negative on a −1 to +1 scale. It reads formal financial text well — around 89% agreement with human labels in reported benchmarks — and slips on the sarcasm and irony common on social platforms, closer to 70%, so we treat every score as an estimate, not a verdict.
Roll it up
Mentions are normalised to a canonical ticker and rolled into hourly and daily figures — volume, net sentiment, and the bull / neutral / bear split. As they are aggregated, low-trust and bot-like accounts are down-weighted, and coordinated spikes are screened by testing author diversity against volume. Every figure is shown with the sample size behind it.
Scores run from −1.00 to +1.00. They describe the balance of bullish and bearish mentions, never a price target. Always read a score with the mention count beside it: the same +0.40 means very different things at 50 mentions and at 5,000.
Where the data comes from
Most of what you see, we compute ourselves. Where we lean on an outside source, here is exactly what it is — and what it may and may not do.
What we don’t show yet
Some figures you would expect on a finance site aren’t here, because we won’t invent them. Until each one is wired to a real, verifiable source, we leave the space empty rather than fill it with a guess.
- International market figures — coverage is expanding country by country; where a per-market number is still illustrative, we mark it, or hold it back until its feed lands.
A blank where a number should be is a promise, not an oversight.
Accuracy is the product.
Every correction, and the date it was made, stays on the affected piece. Pipeline-generated figures are always labelled. If you believe a number is wrong, tell us.