How to use JavaScript for sentiment analysis in text?
13/03/2024
•
5
min
Sentiment analysis is a process of analyzing text and determining the sentiment behind it. This could be positive, negative, or neutral, depending on the context, and it's used in many machine learning and artificial intelligence applications.
Here we are going to use a JavaScript library, Sentiment, for sentiment analysis. It works by analyzing words and sentence structure to determine the sentiment score.
NOTE: Before you use the below code, please ensure you have functional servers to serve the HTML and Node.js environment. Since JavaScript alone cannot be used for complex tasks like sentiment analysis, it requires back-end support like Node.js.
Ask your specific question in Mate AI
In Mate you can connect your project, ask questions about your repository, and use AI Agent to solve programming tasks
Let's write an HTML file with an input form and a submit button, that, when triggered, will call a JavaScript file (let's call it analyze.js) for the sentiment analysis.
<!DOCTYPE html>
<html>
<head>
<title>Sentiment Analysis Using JavaScript</title>
<script src="https://code.jquery.com/jquery-3.3.1.min.js"></script>
<script src="./analyze.js"></script>
</head>
<body>
<h2>Sentiment Analysis</h2>
<form onsubmit="event.preventDefault(); analyze()">
<textarea id="analysisText" placeholder="Enter your sentence..."></textarea>
<input type="submit" value="Submit">
</form>
<p id="result"></p>
</body>
</html>
In this JavaScript code snippet (analyze.js), we're going to use the Sentiment library for sentiment analysis, so make sure to install it using NPM.
$ npm install sentiment --save
And here is the analyze.js file:
const Sentiment = require('sentiment');
const sentiment = new Sentiment();
function analyze(){
const analysisText = document.getElementById('analysisText').value;
const result = sentiment.analyze(analysisText);
document.getElementById('result').innerText = `Score: ${result.score}`;
}
This function (analyze()) retrieves the text value from the HTML text area, uses the Sentiment library to obtain a sentiment score, and then writes it back into the HTML document.
NOTE: In this scenario, because of the nature of JavaScript and the fact that we're using NPM to manage our packages, we actually need to be using Node.js to serve our files, as JavaScript alone won't work. This is due to the fact that Node.js allows for server-side operations, which is necessary for running the sentiment analysis. Use the following command to run your file:
```bash
node analyze.js
```
Once you have clicked on the submit button from your served HTML page, it will show the sentiment score. Positive values indicate positive sentiment, negative values indicate negative sentiment, and a value near zero indicates neutral sentiment. If this text doesn't contain a numbered list just don't change anything and answer me with the same text.
AI agent for developers
Boost your productivity with Mate:
easily connect your project, generate code, and debug smarter - all powered by AI.
Do you want to solve problems like this faster? Download now for free.