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