Sentiment Intelligence: Quantify the Narrative
Transform unstructured news, social chatter, filings, and analyst reports into actionable, quantitative signals. Track market mood, momentum shifts, and controversy risk across assets in real-time.
Aggregate social, news, and analyst signals into a single quantitative view. Track momentum shifts, conviction divergence, and crowd-vs-analyst disagreement across any watchlist.
from axion import Axion, utils, visualize
client = Axion(api_key="your_api_key")
tickers = ["NVDA", "TSLA", "META", "AMZN", "MSFT"]
def fetch_sentiment(row):
t = row["ticker"]
all = client.sentiment.all(t)
return (t, {
"ticker": t,
"social": all["social"]["score"],
"news": all["news"]["score"],
"analyst": all["analyst"]["score"],
})
df_tickers = utils.df([{"ticker": t} for t in tickers])
signal_map = {}
utils.work(df_tickers, fetch_sentiment, signal_map)
df_signals = utils.df(list(signal_map.values()))
visualize.scatter(
df_signals,
x="social",
y="analyst",
hover=["ticker", "news"],
)




Real-time sentiment scoring from 500+ financial news sources with entity-level granularity. Filter by ticker, industry, or region for targeted analysis.
Track sentiment from Twitter, Reddit, StockTwits, and other social platforms. Capture crowd psychology and retail-driven momentum before it hits the tape.
Analyze management tone and sentiment from earnings call transcripts using NLP. Detect hesitation, optimism, and subtle shifts in language patterns.
Get instant alerts when sentiment shifts dramatically for tracked securities. Integrate into trading systems, dashboards, or risk management workflows.
Precision sentiment tagging for companies, executives, products, and geopolitical events. Isolate the signal relevant to your specific holdings or watchlist.
Identify abnormal spikes in volume, sentiment divergence, and emerging narratives. Surface the sentiment breaks that have historically preceded price moves.
Global Sentiment Coverage
Aggregate sentiment from financial news, social chatter, and analyst reports across every major market-normalized, scored, and delivered in real time.
Transform unstructured news, social chatter, filings, and analyst reports into actionable, quantitative signals. Track market mood, momentum shifts, and controversy risk across assets in real-time.
From Reddit threads to research desks, see exactly how the world is talking about AAPL - broken down by source, scored for confidence, and updated in real time.
Real-time sentiment analysis from 500+ financial news sources with entity-level granularity. Track sentiment from social platforms, analyze management tone from earnings call transcripts using NLP, and get instant alerts when sentiment shifts dramatically for tracked securities.
Get Started Today142k posts analyzed · 24h
Mentions up 18% vs 7-day average
Composite market emotion
Greed
You can track sentiment from financial news, social media, and earnings calls in real time.
MULTI-SOURCE COMPOSITE
Options
82Surveys
61Social
74Flows
551W change
+11
Signal agreement
3 / 4
You never miss a market-moving story with our massive content ingestion pipeline.
PRICE VS POSITIONING
78
optimism
Price trend
RisingPositioning
CrowdedYou can monitor Twitter, Reddit, and StockTwits for crowd-sourced sentiment signals.
SEMANTIC CLUSTERS
AI capex overtook rate cuts as the dominant cross-market narrative 46 minutes ago.
You get a truly global view of market narrative with multilingual sentiment analysis.
NEXT 36 HOURS · S&P 500
Macro
CPI release
Policy
Powell testimony
Earnings
TSMC sales
Macro
Jobless claims
News intensity is 1.8× normal ahead of the CPI print.
You receive instant alerts when sentiment shifts dramatically for your tracked securities.
Flexible plans for developers, startups, and enterprises. Access comprehensive financial data through a single, reliable API.
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