Python Code Example

This Python script demonstrates how to use the Sentiment Analyser API to analyze the sentiment of a specific text. The script utilizes the requests library to make an HTTP GET request to the API, which then returns a sentiment analysis as a JSON response.

import requests

# Set the API endpoint URL
url = "https://sentiment-analyzer3.p.rapidapi.com/Sentiment"

# Define the query parameters with the text to be analyzed
querystring = {"text": "Good Morning"}

# Include the necessary headers, including your RapidAPI key and host information
headers = {
    "X-RapidAPI-Key": "{YOUR-API-KEY}",
    "X-RapidAPI-Host": "sentiment-analyzer3.p.rapidapi.com"
}

# Send the GET request and capture the response
response = requests.get(url, headers=headers, params=querystring)

# Print the JSON response from the API
print(response.json())

JSON Response Format

The Sentiment Analyser API provides a detailed JSON object that quantifies the sentiment of the provided text. Below are descriptions of each component in the JSON response:

• neg: Float value representing the percentage of the analyzed text that was deemed negative. A value of 0.0 indicates an absence of negative sentiment.

• neu: Float value indicating the percentage of the text considered neutral. For instance, 25.6% of the text in the example is neutral.

• pos: Float value showing the percentage of the text recognized as positive. In this example, 74.4% of the text is positive.

• compound: A normalized compound score that sums all lexicon ratings which have been standardized to fall between -1 (most negative) and +1 (most positive). The score of 0.4404 suggests a predominantly positive sentiment.

• sentiment: A string that categorizes the overall sentiment of the text based on the analysis. Possible values include “Positive,” “Negative,” or “Neutral.” In this case, the sentiment is “Positive”.

Example JSON Response:

{
  "neg": 0.0,
  "neu": 0.256,
  "pos": 0.744,
  "compound": 0.4404,
  "sentiment": "Positive"
}