In this tutorial, you will learn how to use Sentiment Analysis API in 5 minutes using Python and Eden AI Sentiment Analysis API. Eden AI provides an easy and developer-friendly API that allows you to detect sentiment in texts.
Sentiment Analysis is a NLP (Natural Language Processing) process that tracks and categorizes the public’s mood and opinion in a conversation. Also known as opinion mining, it can be automated using machine learning to detect and extract positive, negative, or neutral sentiment from text.
Sentiment Analysis can be found in many domains, such as marketing or social media. For instance, it can help your marketing team to understand the type of feeling that your brand or product generates so they can proactively manage the image of your brand, thus transforming your customer experience.
If you want to learn more about what NLP can offer, check out our selection of the Best Natural Language Processing APIs.
Also, if you are wondering what differenciates Sentiment Analysis from Custom Text Classification, we recommand reading Sentiment Analysis vs. Custom Text Classification APIs : which one to choose.
The first step to using Sentiment Analysis is to install Python's requests package, that will allow you to call Eden AI API.
Next, you'll need to install Python's JSON package in order to be able to read and print the result of the API request.
You are now ready to process text into Eden AI Sentiment Analysis 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.
Now that you have imported packages on Python 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.
Here is the Python script you need to write on your notebook:
As shown above, we called two different Sentiment Analysis engines. Eden AI API will then return in its JSON response results of those providers. Once the request is done, you will be able to get the result with this print:
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.
In this article, we explain how the mapping between the input language and the languages supported by the providers is performed to facilitate access to one of our AI engines.