brms
for data scientists, R developers
Why this scored 11
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.
- 117
brm model running, no error, no result, when including file = "path/filename"
Model runs without output when file paths are included, indicating a loading issue. · for data scientists, R developers
stackoverflowSteadydata21d ago - 216
Error using normal_gamma() from RegimeChange package with a brms model
normal_gamma error in RegimeChange can break Bayesian brms models, requiring debugging. · for R statisticians
stackoverflowSteadydevtools40d ago - 315
Add prediction draws (function epred_draws) from 2 different models in a single graph
Adds epred_draws to plot predictions from multiple models in one ggplot2 graph. · for r users, data scientists
stackoverflowSteadydata48d ago