yifanfeng97/Hyper-Extract — GitHub trend

FINDING #575 · 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

SURPRISE0.0146

ENGAGEMENT0.20

FRESHNESS1.00

SCORE = SURPRISE × ENGAGEMENT^0.7 × FRESHNESS × VISIBILITY × CONFIDENCE

SURPRISE = WINDOW STARS / DAYS / (AUDIENCE + FLOOR)

2% OF STARS IN ARCHIVE

Growth Telemetry

VELOCITY /D

9.43

ACCEL

-2.29

RETENTION

38.3%

PEAK 2026-07-08 · FORK-RETENTION 0.0% · 66 STARS / WINDOW

Author Audience

AUDIENCE

607

FOLLOWERS

289

OWNER ★

3,180

Engagement Signals

FORKS

367

ISSUE AUTH

PR AUTH

UNIQUE STARGAZERS 66 / 66 (DIVERSITY 1.00)

Why This Is A Finding

yifanfeng97/Hyper-Extract собрал 66 звёзд за окно, тогда как у автора всего 289 подписчиков — эффективная аудитория ≈ 607. Это даёт surprise-индекс 0.0146 (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.

Related Findings

RANKS ABOVE 49% OF 1120 FINDINGS

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METRICS IN CONTEXT

MEDIAN ACROSS ALL 1120 FINDINGS · Δ vs MEDIAN · PERCENTILE = SHARE RANKED BELOW

METRICVALUEMEDIANΔ MEDPERCENTILE

SCORE0.000.01-0.00ABOVE 49%

VELOCITY9.4313.86-4.43ABOVE 36%

RETENTION38.3%36.8%+1.5 PPABOVE 53%

FORKS36750+317ABOVE 79%

SURPRISE0.010.04-0.03ABOVE 26%