Github Trends®
1013 findingsmedian surprise 0.0334window 30 days
UNIT / TREND-MONITOR · REV 2.6
[ 30 days window ]
SOURCE: gharchive
РЕПО НЕТ В ОКНЕ 1D. ПОКАЗАН FINDING ИЗ ОКНА 30D (30 days) — РАНГ #723.
FINDING #723 · UNIT ID 1129583447
yifanfeng97/Hyper-Extract
Hypergraph is more powerful. Transform unstructured text into structured knowledge with LLMs. Graphs, hypergraphs, and spatio-temporal extractions — with one command.
[ PYTHON ][ GITHUB ↗ ]
SURPRISE SCORE
0.00

Score Breakdown

SURPRISE0.10
ENGAGEMENT0.20
FRESHNESS1.34
SCORE = SURPRISE × ENGAGEMENT^0.7 × FRESHNESS × VISIBILITY × CONFIDENCE
SURPRISE = WINDOW STARS / DAYS / (AUDIENCE + FLOOR)
64% OF STARS IN ARCHIVE
[BOT] SUSPECTED STAR BOT — SCORE PENALIZED. SIGNATURES:
S2 · NO EXTERNAL ISSUE/PR AUTHORS DESPITE 100+ STARS
S5 · PREDATES WINDOW, YET HALF+ OF ALL ITS STARS LANDED IN IT
S7 · THIS REPO IS ~ALL OF THE OWNER'S STARS

Growth Telemetry

VELOCITY /D
65.60
ACCEL
-5.65
RETENTION
18.5%
PEAK 2026-06-17 · FORK-RETENTION 0.0% · 1,968 STARS / WINDOW

Author Audience

AUDIENCE
607
FOLLOWERS
289
OWNER ★
3,180

Engagement Signals

FORKS
367
ISSUE AUTH
0
PR AUTH
0
UNIQUE STARGAZERS 1,968 / 1,968 (DIVERSITY 1.00)

Why This Is A Finding

yifanfeng97/Hyper-Extract собрал 1,968 звёзд за окно, тогда как у автора всего 289 подписчиков — эффективная аудитория ≈ 607. Это даёт surprise-индекс 0.10 (звёзды относительно охвата автора, а не в абсолюте). Удержание форков 0.0% и 0 внешних контрибьюторов отделяют реальный инструмент от разовой вспышки. Акселерация отрицательная — внимание остывает после пика.

METRICS IN CONTEXT

MEDIAN ACROSS ALL 1013 FINDINGS · Δ vs MEDIAN · PERCENTILE = SHARE RANKED BELOW
METRICVALUEMEDIANΔ MEDPERCENTILE
SCORE0.000.00-0.00ABOVE 29%
VELOCITY65.607.20+58.40ABOVE 86%
RETENTION18.5%30.8%-12.2 PPABOVE 26%
FORKS36756+311ABOVE 78%
SURPRISE0.100.03+0.07ABOVE 86%