News Sentiment: AI Summaries as Signals
What is news sentiment analysis?
News sentiment analysis automatically processes current news about a stock using AI — and classifies it as bullish, bearish or neutral. No more manual news reading: the system filters relevant stories, ignores noise and delivers a clear signal.
What gets analyzed
| News type | Example | Typical impact |
|---|---|---|
| Earnings surprise | Profit +30 % above estimate | Strongly bullish |
| Analyst upgrade | Upgraded to "Buy" | Moderately bullish |
| CEO resignation | Unexpected departure | Bearish |
| FDA approval | Drug gets approved | Strongly bullish (biotech) |
| Profit warning | Revenue below guidance | Bearish |
| Share buyback | $500M buyback announced | Bullish |
| Antitrust investigation | DOJ proceedings initiated | Bearish |
| M&A rumor | Acquisition at premium | Strongly bullish |
How the AI analysis works
Step 1: News from the past 7 days is collected via API
Step 2: GPT-4o-mini reads the headline + summary of each story
Step 3: Classification: Bullish / Bearish / Neutral + confidence 0–100 %
Step 4: Weighted average of all stories → news sentiment score
Step 5: Long / Short / Neutral signal
Older news is weighted less — a story from yesterday counts more than one from 6 days ago.
Signal interpretation
| Score | Signal |
|---|---|
| > 65 % bullish | Long |
| 40 – 65 % bullish | Neutral |
| < 40 % bullish | Short |
Additionally: stories with very high confidence (> 85 %) and a clear tone are flagged as high-impact events and can outweigh signals from other methods.
Difference between news sentiment and WSB sentiment
| News sentiment | WSB sentiment | |
|---|---|---|
| Source | Financial news (Reuters, Benzinga, SEC filings) | selection universe from r/WallStreetBets posts & comments |
| Author | Journalists, analysts | Retail traders, memes |
| Time window | 7 days | Weekend |
| Type | Factual | Emotional / speculative |
Both signals together create a complete picture: what the news world says and what retail traders think.
Limitations of news sentiment analysis
- AI can misinterpret sarcasm and irony in headlines
- Paid-for research (sponsored analysis) can bias sentiment
- Breaking news during the trading day is only captured in the next weekly run
- News APIs have varying coverage — not all sources are equally comprehensive
All 8 methods → | WSB sentiment → | Liquidity analysis → | Pricing →