dataentity · corroborated across sources

numpy

for data scientists

Steady

signal score

live items

→ Steady

7-day est. ~0

stackoverflow

Why this scored 0

every term, weighted

Velocity+0.0 / 40 max

Engagement per hour, normalized against the fastest item on its own source

Acceleration+0.0 / 25 max

Whether that velocity is itself speeding up, as a per-hour rate

Cross-source spread+0.0 / 25 max

How many independent communities are talking about the same entity

Recency+1.4 / 10 max

Decays to zero over 14 days

Saturation penalty−3.8 / 30 max

Subtracted once something is big and old — we rank what's next, not what's peaked

Composite-2.4 → clamped to 0

Weights are hand-tuned, not learned — we're calibrating them against realized trends as history accumulates. On a topic's first sighting there's no previous reading to compare against, so acceleration starts from a neutral prior rather than a measurement. Full methodology

Outlook

high confidence · estimate, not a guarantee

7-day

range 0–0

14-day

range 0–0

30-day

range 0–0

Signal history

7-day window (free)

— — projected trajectory (estimate, not a guarantee)

The evidence

The live items this entity's score aggregates — every community independently talking about it right now. This is the corroboration, shown, not claimed.