Tutorial
Text Processing
8 min reading

How to do Sentiment Analysis with JavaScript?

Summarize this article with:

summary
  • Sentiment analysis is a technique in natural language processing that aims to identify and classify the sentiment expressed in a piece of text as positive, negative, or neutral.
  • This process can be automated using machine learning algorithms to analyze text and extract sentiment.
  • You can process Sentiment Analysis in many languages.
  • Developers can do Sentiment Analysis with JavaScript using a REST API that accepts standard inputs and returns structured JSON responses.
  • The integration works with Python, JavaScript, PHP, and any HTTP-capable language with minimal setup.

In this tutorial, you will learn how to use Sentiment Analysis API in 5 minutes using JavaScript. Eden AI provides an easy and developer-friendly API that allows you to detect sentiment in texts.

What is Sentiment Analysis ?

Sentiment analysis is a technique in natural language processing that aims to identify and classify the sentiment expressed in a piece of text as positive, negative, or neutral.

This process can be automated using machine learning algorithms to analyze text and extract sentiment. Sentiment analysis is used in a variety of fields, such as marketing and social media, to understand how people feel about a particular brand or product.

If you want to learn more about natural language processing, you can check out our list of the best natural language processing APIs. Additionally, if you are trying to decide between sentiment analysis and custom text classification, you may want to read our comparison of sentiment analysis vs. custom text classification APIs.

Example of Sentiment Analysis results on Eden AI platform

Getting Started with Sentiment Analysis API

The first step is to set Axios, a promise-based HTTP client for the browser and Node.js, that will allow you to call Eden AI API.

How to use Sentiment Analysis API with JavaScript

You can process Sentiment Analysis in many languages. You can access the list of languages supported in our documentation here, or have a look at our Top 10 Sentiment Analysis APIs

1. Get a Sentiment Analysis API Key on Eden AI

To perform Sentiment Analysis, you'll need to create an account on Eden AI for free. Then, you will be able to get your API key direclty from the homepage with free credits offered by Eden AI.

Get your API key for FREE on Eden AI

2. Let’s Analyze Sentiment in Text

Now that you have imported packages on JavaScript and got your API key, you will be able to detect sentiment in your text. With Eden AI, you can choose from a wide range of different engines you want for Sentiment Analysis.

To help you choose the best provider according to your needs and type of project, feel free to browse our list of Sentiment Analysis providers.

For example, we called two different Sentiment Analysis engines. Here is the JS code to configure the request:

Then, you just need to launch the request and print the result:

Here is an example of a Sentiment Analysis API response:

Benefits of using Sentiment Analysis API with Eden AI

Using Sentiment Analysis with Eden AI API is quick and easy.

Best Sentiment Analysis AIs in one API

Save time and cost

We offer a unified API for all providers: simple and standard to use, with a quick switch between providers and an access to the specificic features of each provider

Easy to integrate

The JSON output format is the same for all suppliers thanks to Eden AI's standardisation work. The response elements are also standardised thanks to Eden AI's powerful matching algorithms.

Customization

With Eden AI you have the possibility to integrate a third party platform: we can quickly develop connectors. To go further and customize your Sentiment Analysis request with specific parameters, check out our documentation.

FAQ — do Sentiment Analysis with JavaScript

You need an API key from your chosen AI provider. Eden AI lets you access multiple providers with a single key, removing the need for separate vendor accounts.
Any language that supports HTTP requests works — Python, JavaScript, PHP, Ruby, Go, and more. Ready-to-use code snippets are available for the most common languages.
Most developers complete a basic integration in under an hour using standardized API endpoints and ready-to-use code examples.
Implement exponential backoff for rate limit errors and use try-catch blocks for network failures. Eden AI's built-in fallback routing automatically redirects requests if a provider is unavailable.
Eden AI supports GDPR-compliant provider filtering and does not store or reuse your data, ensuring compliance with European privacy regulations.

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