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sarcasm-detector

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  • License MIT

A library for detecting sarcasm and tone in text using pattern matching and linguistic rules

Package Exports

  • sarcasm-detector
  • sarcasm-detector/index.js

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Readme

Sarcasm Detector

A JavaScript library for detecting sarcasm and tone in text using pattern matching and linguistic rules.

Installation

npm install sarcasm-detector

Usage

const SarcasmDetector = require('sarcasm-detector');

const detector = new SarcasmDetector();

// Detect sarcasm
const sarcasmResult = detector.detectSarcasm("Oh great, another meeting that could have been an email");
console.log(sarcasmResult);
// {
//   isSarcastic: true,
//   confidence: 0.8,
//   sentiment: 2,
//   indicators: {
//     patternMatches: true,
//     hasExaggeration: false,
//     hasIrony: false,
//     hasPositiveSentimentWithNegativeContext: true
//   }
// }

// Detect tone
const toneResult = detector.detectTone("I'm really disappointed with the service");
console.log(toneResult);
// {
//   tone: 'negative',
//   confidence: 0.6,
//   sentiment: -3,
//   isSarcastic: false
// }

Features

  • Sarcasm detection using multiple indicators:
    • Common sarcasm patterns
    • Exaggeration words
    • Irony indicators
    • Sentiment analysis
  • Tone detection:
    • Positive
    • Negative
    • Neutral
    • Sarcastic
    • Slightly positive/negative
  • Confidence scoring for both sarcasm and tone detection

How It Works

The library uses a combination of techniques to detect sarcasm and tone:

  1. Pattern matching for common sarcastic phrases
  2. Detection of exaggeration words
  3. Identification of irony indicators
  4. Sentiment analysis to detect positive statements with negative context
  5. A weighted scoring system to determine the likelihood of sarcasm

Limitations

  • This is a rule-based approach and may not catch all instances of sarcasm
  • Performance depends on the quality of the input text
  • May produce false positives in some cases
  • Works best with clear, well-structured sentences

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

MIT