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  • License MIT

A lightweight and easy-to-use npm package for performing sentiment analysis on text. Analyze the positivity, negativity, or neutrality of any string input with ease, and process multiple texts in batch for more efficient analysis.

Package Exports

    This package does not declare an exports field, so the exports above have been automatically detected and optimized by JSPM instead. If any package subpath is missing, it is recommended to post an issue to the original package (sentiment-analyze) to support the "exports" field. If that is not possible, create a JSPM override to customize the exports field for this package.

    Readme

    A lightweight and easy-to-use npm package for performing sentiment analysis on text. Analyze the positivity, negativity, or neutrality of any string input with ease, and process multiple texts in batch for more efficient analysis.

    🌟 Features

    • Simple and intuitive API for sentiment analysis.
    • Returns detailed sentiment results (score, comparative, positive words, negative words).
    • Batch analysis for processing multiple texts at once.
    • Emotion detection that categorizes sentiment as happiness, sadness, or neutral.
    • Lightweight and efficient, with minimal dependencies.

    ❤️ Support My Work!

    Maintaining this package requires effort and dedication. If this project helped you, consider buying me a coffee or supporting me via PayPal. Every donation helps keep this project alive!

    Support via PayPal

    📦 Installation

    Install the package via npm:

    npm install sentiment-analyze

    🚀 Usage

    Here's how to use the sentiment-analyze package in your Node.js project:

    Example 1: Basic Sentiment Analysis

    // Import the SentimentAnalyze
    const { SentimentAnalyze } = require('sentiment-analyze');
    
    // Create an instance of SentimentAnalyzer
    const analyzer = new SentimentAnalyze();
    
    // Analyze a text string
    const result = analyzer.analyze('I love programming but hate bugs.');
    
    console.log(result);
    // Output:
    // {
    //   score: 0,
    //   comparative: 0,
    //   positive: ['love'],
    //   negative: ['hate']
    // }

    Example 2: Batch Sentiment Analysis

    // Create an instance of SentimentAnalyzer
    const analyzer = new SentimentAnalyze();
    
    // Analyze multiple texts in batch
    const batchResult = analyzer.batchAnalyze([
      'I am happy with my work.',
      'This is such a terrible day.',
      'I feel neutral about this.'
    ]);
    
    console.log(batchResult);
    // Output:
    // [
    //   { score: 2, comparative: 0.4, positive: ['happy'], negative: [] },
    //   { score: -2, comparative: -0.4, positive: [], negative: ['terrible'] },
    //   { score: 0, comparative: 0, positive: [], negative: [] }
    // ]
    
    

    Example 3: Emotion Detection

    // Create an instance of SentimentAnalyzer
    const analyzer = new SentimentAnalyze();
    
    // Detect emotion in a sentence
    const emotionResult = analyzer.detectEmotion('I am feeling great today!');
    console.log(emotionResult);
    // Output:
    // {
    //   emotion: 'happiness',
    //   score: 2
    // }
    

    📊 Output Format

    The result object contains the following fields:

    • score: Overall sentiment score (positive or negative)
    • comparative: Comparative score relative to the text length.
    • positive: Array of positive words detected.
    • negative: Array of negative words detected.

    For emotion detection:

    • emotion: The detected emotion (happiness, sadness, or neutral).
    • score: A numeric score that indicates the overall sentiment intensity.

    🔧 Methods

    analyze(text: string)

    Analyzes the sentiment of the given text.

    Parameters:

    • text (string): The text to analyze.

    Returns:

    An object containing:

    • score: Sentiment score (number).
    • comparative: Comparative sentiment score (number).
    • positive: Array of positive words (string[]).
    • negative: Array of negative words (string[]).
    batchAnalyze(texts: string[])

    Analyzes an array of text strings in batch.

    Parameters:

    • texts (string[]): An array of texts to analyze.

    Returns:

    An array of sentiment results for each text, each containing:

    • score: Sentiment score (number).
    • comparative: Comparative sentiment score (number).
    • positive: Array of positive words (string[]).
    • negative: Array of negative words (string[]).
    detectEmotion(text: string)

    Detects the emotion of the given text based on positive and negative word lists.

    Parameters:

    • text (string): The text to analyze.

    Returns:

    An object containing:

    • emotion: The detected emotion (happiness, sadness, or neutral).
    • score: A numeric score indicating the overall sentiment intensity.

    📝 License

    This project is licensed under the MIT License. See the LICENSE file for details.