📚 Documentation & Examples
Everything you need to integrate with Sentiment Analysis
🚀 Quick Start Examples
// Sentiment Analysis API Example
const response = await fetch('https://www.meaningcloud.com/developer/sentiment-analysis', {
method: 'GET',
headers: {
'Content-Type': 'application/json'
}
});
const data = await response.json();
console.log(data);The Multilingual Sentiment Analysis API provides advanced capabilities for analyzing the sentiment of texts written in various languages. This API is designed to process and interpret the emotional tone within textual data sourced from social media, reviews, news articles, and more. By leveraging cutting-edge natural language processing technology, users can gain insights into public opinion and sentiment trends across different cultures and languages, making it an invaluable tool for businesses and researchers aiming to enhance customer satisfaction, brand reputation, and market understanding. For more detailed information on integration, users can refer to the official documentation at MeaningCloud Sentiment Analysis.
Utilizing the Multilingual Sentiment Analysis API offers numerous advantages, including the ability to analyze textual data in multiple languages, which broadens the scope of sentiment evaluation. The API is fast and efficient, enabling real-time processing of large volumes of text. It provides comprehensive sentiment scoring, allowing users to differentiate between positive, negative, and neutral sentiments. Additionally, the API features easy integration with a variety of programming languages, and its scalability supports both small projects and enterprise-level applications. Here’s a JavaScript code snippet for making a call to the API:
const axios = require('axios');
const apiKey = 'YOUR_API_KEY';
const text = 'I love using this product!';
axios.post('https://api.meaningcloud.com/sentiment-2.1', null, {
params: {
key: apiKey,
txt: text,
lang: 'en'
}
})
.then(response => {
console.log('Sentiment Analysis Result:', response.data);
})
.catch(error => {
console.error('Error calling the API:', error);
});
