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AXION

Sentiment Analysts

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GET/sentiment/:ticker/analyst

Provides AI-powered sentiment analysis of analyst reports, research notes, and investment recommendations. Offers insights into professional analyst sentiment and forward-looking perspectives on the company.

Path Parameters

ParameterTypeRequiredDescription
tickerstringRequiredStock ticker symbol (e.g., "AAPL", "TSLA", "MSFT")

Examples:

https://api.axionquant.com/sentiment/AAPL/analyst
https://api.axionquant.com/sentiment/MSFT/analyst

Response Fields

sentiment string

Analyst sentiment label (POSITIVE/NEGATIVE)

score number

Confidence score (0.0-1.0)

|

Analyst Sentiment

Request

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

Response

{
  "sentiment": "NEGATIVE",
  "score": 0.31
}
GET/sentiment/:ticker/news

Analyzes sentiment from financial news articles and press releases. Provides insights into how traditional media is covering the company, including earnings reports, product announcements, and corporate developments.

Path Parameters

ParameterTypeRequiredDescription
tickerstringRequiredStock ticker symbol (e.g., "AAPL", "TSLA", "MSFT")

Examples:

https://api.axionquant.com/sentiment/TSLA/news
https://api.axionquant.com/sentiment/AAPL/news

Response Fields

Same structure as Social Media Sentiment response.

label string

Overall sentiment label (POSITIVE/NEGATIVE)

score number

Confidence score (0.0-1.0)

breakdown

Breakdown of positive/negative segments with counts and average scores

|

News Sentiment

Request

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

Response

{
  "label": "NEGATIVE",
  "score": 0.982357367873192,
  "breakdown": {
    "positive": {
      "count": 231,
      "avgScore": 0.903340172767639
    },
    "negative": {
      "count": 1292,
      "avgScore": 0.982357367873192
    }
  }
}
GET/sentiment/:ticker/social

Analyzes sentiment from social media platforms including Google search trends, Twitter/X conversations, and Reddit discussions. Provides real-time insights into public perception and trending topics related to the company.

Path Parameters

ParameterTypeRequiredDescription
tickerstringRequiredStock ticker symbol (e.g., "AAPL", "TSLA", "MSFT")

Examples:

https://api.axionquant.com/sentiment/AAPL/social
https://api.axionquant.com/sentiment/TSLA/social

Response Fields

label string

Overall sentiment label (POSITIVE/NEGATIVE)

score number

Confidence score (0.0-1.0)

breakdown

Detailed breakdown of positive and negative segments

positive

Contains count and avgScore for positive sentiment

negative

Contains count and avgScore for negative sentiment

|

Social Media Sentiment

Request

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

Response

{
  "label": "NEGATIVE",
  "score": 0.99506558974584,
  "breakdown": {
    "positive": {
      "count": 145,
      "avgScore": 0.93158021569252
    },
    "negative": {
      "count": 436,
      "avgScore": 0.99506558974584
    }
  }
}