Market Sentiment

Ticker-level sentiment from four sources; social media, news flow, journalist tone and analyst commentary; so you can test which signal carries alpha for your strategy.

Aggregate Sentiment Score Analyst Tone Journalist Coverage Tone Social Media Sentiment

Sentiment API

The Sentiment API provides comprehensive sentiment analysis across social media, news articles, and analyst reports for public companies. These insights are essential for gauging market sentiment, identifying emerging trends, and understanding public perception of specific stocks.

GET/sentiment/:ticker/all

Retrieves comprehensive sentiment analysis across three key data sources: social media (Google, Twitter, Reddit), financial news, and AI-powered analyst reports. This aggregated view provides a holistic understanding of market sentiment towards a specific company.

Path Parameters

Parameter	Type	Required	Description
ticker	string	Required	Stock ticker symbol (e.g., "AAPL", "TSLA", "MSFT")

Examples:

https://api.axionquant.com/sentiment/AAPL/all

https://api.axionquant.com/sentiment/MSFT/all

Response Fields

socialSentiment

Object containing social media sentiment analysis

label string

Overall sentiment label (POSITIVE/NEGATIVE)

score number

Confidence score (0.0-1.0)

breakdown

Detailed breakdown of positive/negative segments

newsSentiment

Object containing financial news sentiment analysis (same structure as socialSentiment)

analystSentiment

Object containing AI-powered analyst sentiment

sentiment string

Analyst sentiment label (POSITIVE/NEGATIVE)

score number

Confidence score (0.0-1.0)

All Sentiment Data

Request

Sample code

1from axion import Axion
2client = Axion(api_key='axn_123')
3
4sentiment = client.sentiment.all('AAPL')
5print(sentiment)

Response

{
  "socialSentiment": {
    "label": "NEGATIVE",
    "score": 0.979367434978485,
    "breakdown": {
      "positive": {
        "count": 0,
        "avgScore": 0
      },
      "negative": {
        "count": 100,
        "avgScore": 0.979367434978485
      }
    }
  },
  "newsSentiment": {
    "label": "NEGATIVE",
    "score": 0.952301025390625,
    "breakdown": {
      "positive": {
        "count": 10,
        "avgScore": 0.875148761272431
      },
      "negative": {
        "count": 16,
        "avgScore": 0.952301025390625
      }
    }
  },
  "analystSentiment": {
    "sentiment": "POSITIVE",
    "score": 0.66
  }
}