NewJev X Sentiment Analysis
It combines market microstructure with stratified social evidence in one structured decision request, with separate typed outputs for recommendation, sentiment, squeeze risk and news impact.
Added to Jevfast
NewHow it uses Jev
The on-demand analysis fetches market data and a requested sample of posts, statistically aggregates sentiment and selects representative tweets, then sends structured market/social state to Jev. Jev returns a Choice trading action, Score sentiment and catalyst impact, and Noul squeeze risk. The service maps those typed answers into a trade ticket/dashboard response.
What Jev decides
Market and sentiment actionExample answers · not a recorded Jev response · Source ↗
Question 1 · trade action
YOUR APP
INSTRUCTION
Choose the best immediate trading action from market data and social sentiment.
STATE
State includes asset, market fields (price/change/momentum/RSI/perpetuals/funding/open-interest/volume), social aggregate fields and representative tweet sample.
JEV · CHOICE
- STRONG_BUY
- BUY
- HOLD
- TAKE_PROFIT
- SELL
- STRONG_SELL
Question 2 · is short squeeze risk
YOUR APP
INSTRUCTION
Given perpetual funding and social panic at support, or extreme oversold RSI with panic if perpetual data is unavailable, is there short-squeeze/capitulation-bounce risk?
STATE
State includes asset, market fields (price/change/momentum/RSI/perpetuals/funding/open-interest/volume), social aggregate fields and representative tweet sample.
JEV · NOUL
YesNo
App workflow
- Submit analysis request
Provide symbol and sample size (50–1000 posts; default 100).
- Fetch source data
Fetch market data and requested posts concurrently.
- Aggregate social evidence
Compute statistics and a stratified representative sample.
- Evaluate with Jev
Send state and four typed questions to System One.
- Build decision output
Map answers into recommendation, confidence, sentiment and risk/catalyst metrics.
Why it is interesting
It combines market microstructure with stratified social evidence in one structured decision request, with separate typed outputs for recommendation, sentiment, squeeze risk and news impact.