streamlit
for data engineers, web devs
Why this scored 0
every term, weightedIts fastest-moving item, measured against the pace of its own source
Whether that velocity is itself speeding up, as a per-hour rate
How many independent communities its own items come from
Decays to zero over 14 days, counted from when we first saw it
Subtracted once something is big and old — sized by its biggest item, aged from when we first saw it
Weights are hand-tuned, not learned — we're calibrating them against realized trends as history accumulates. On an entity's first sighting there's no previous reading to compare against, so acceleration starts from a neutral prior rather than a measurement, and velocity falls back to engagement over its whole lifetime until a second reading exists. Full methodology
Signal history
7-day window (free)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.
- 110
Building an Interactive South America Dashboard with Streamlit and World Bank Data
Streamlit dashboard using World Bank data enables quick South America visual analytics. · for data engineers, web devs
devtoCoolingdata1h ago - 20
uajy-academic-rag-chatbot — Production-grade RAG chatbot for Universitas Atma Jaya Yogyakarta academic handbook with Streamlit, FAISS vector
Production-grade RAG chatbot for a university handbook built with Streamlit and FAISS. · for AI engineers, academic developers
githubSteadyai−16 saturated11d ago