How our scoring works
Most trend tools read lagging search data and hand you a graph. We read the leading edge — developer and builder communities — and score real momentum. Here's exactly how, because a score you can't interrogate isn't worth trusting.
The sources
Every hour we ingest Hacker News, GitHub, Dev.to, Lobsters, Product Hunt, and news signals. These are where technical trends actually start — weeks before they show up in mainstream search-trend tools. We deliberately favor leading indicators over lagging ones.
The signal score (0–100)
Each topic's score is a weighted blend of four things:
Velocity
How fast attention is growing right now — not just how popular something is. A repo going 50→400 stars/day beats one sitting flat at 5,000.
Acceleration
Whether that growth is speeding up. Early-stage momentum scores highest; this is what catches trends on the way up.
Cross-source spread
How many independent communities mention the same entity. This is the anti-hype filter — one viral thread isn't a trend; corroboration is.
Recency & saturation
Newer topics get a boost; already-mainstream, peaked topics get down-ranked so you see what's next, not what's over.
The anti-hype filter (our edge)
The hard part of trend detection isn't finding things — it's filtering noise. We use an LLM to extract the canonical entities from every headline (merging aliases like "Claude Code" → "Claude"), then measure how many distinct sources independently mention each one. A topic only earns a high spread score when unrelated communities agree. That's the difference between a real movement and a single loud post.
Lifecycle stages
As we accumulate history, each topic is labelled by where it is in its arc: Emerging (new and rising), Heating (accelerating), Peaking (high and flattening), and Cooling (past its moment). You get in early, not late.
Honest limits
Forecasts are estimates from recent momentum, not guarantees. Acceleration and lifecycle need a few data points to be meaningful, so brand-new topics show as "Emerging" until history builds. We'd rather tell you that than fake precision.
See the method in action.
Open the live feed →