AI Text Detector

A lightweight, fast JavaScript/TypeScript library for detecting AI-generated text using advanced linguistic analysis. Works in both Node.js and browser environments with zero dependencies.

Features

• 🚀 Lightweight - Zero external dependencies, small bundle size
• 🔍 Accurate - Uses 15+ linguistic analysis techniques including perplexity and burstiness
• 🌐 Universal - Works in Node.js, React, Vue, Angular, and browser environments
• 📝 TypeScript - Full TypeScript support with comprehensive type definitions
• ⚡ Fast - Efficient pattern matching and analysis algorithms
• 🧠 Smart - Advanced analysis of sentence structure, vocabulary patterns, and writing style
• 📊 Detailed - Provides confidence scores, reasoning, and detailed metrics

Installation

npm install ai-text-detector

yarn add ai-text-detector

Usage

Basic Usage

import {
  detectAIText,
  isAIGenerated,
  getConfidenceScore,
} from "ai-text-detector";

const text =
  "Furthermore, it is important to note that artificial intelligence has significantly enhanced various operational processes across multiple industries.";

// Get detailed analysis
const result = detectAIText(text);
console.log(result);
// {
//   isAIGenerated: true,
//   confidence: 0.75,
//   reasons: [
//     "High frequency of transition words typical of AI writing",
//     "Elevated formality level characteristic of AI text"
//   ],
//   score: 0.75
// }

// Quick boolean check
const isAI = isAIGenerated(text);
console.log(isAI); // true

// Get just the confidence score
const confidence = getConfidenceScore(text);
console.log(confidence); // 0.75

Node.js Usage

const { detectAIText } = require("ai-text-detector");

const text = "Your text here...";
const result = detectAIText(text);
console.log(result);

React Usage

import React, { useState } from "react";
import { detectAIText } from "ai-text-detector";

function AIDetector() {
  const [text, setText] = useState("");
  const [result, setResult] = useState(null);

  const analyzeText = () => {
    if (text.trim()) {
      const detection = detectAIText(text);
      setResult(detection);
    }
  };

  return (
    <div>
      <textarea
        value={text}
        onChange={(e) => setText(e.target.value)}
        placeholder="Enter text to analyze..."
      />
      <button onClick={analyzeText}>Analyze Text</button>

      {result && (
        <div>
          <p>AI Generated: {result.isAIGenerated ? "Yes" : "No"}</p>
          <p>Confidence: {(result.confidence * 100).toFixed(1)}%</p>
          <ul>
            {result.reasons.map((reason, index) => (
              <li key={index}>{reason}</li>
            ))}
          </ul>
        </div>
      )}
    </div>
  );
}

API Reference

detectAIText(text: string): DetectionResult

Analyzes the provided text and returns a detailed detection result.

Parameters:

• text (string): The text to analyze

Returns:

• DetectionResult object with the following properties:
  • isAIGenerated (boolean): Whether the text is likely AI-generated
  • confidence (number): Confidence score between 0 and 1
  • reasons (string[]): Array of reasons explaining the detection
  • score (number): Raw detection score

isAIGenerated(text: string): boolean

Quick check to determine if text is likely AI-generated.

Parameters:

• text (string): The text to analyze

Returns:

• boolean: True if likely AI-generated, false otherwise

getConfidenceScore(text: string): number

Returns just the confidence score for the detection.

Parameters:

• text (string): The text to analyze

Returns:

• number: Confidence score between 0 and 1

API Reference

detectAIText(text: string): DetectionResult

Analyzes the provided text and returns a comprehensive detection result.

Parameters:

• text (string): The text to analyze

Returns: DetectionResult object with the following properties:

• isAIGenerated (boolean): Whether the text is likely AI-generated
• confidence (number): Confidence score between 0 and 1
• reasons (string[]): Array of reasons for the detection result
• score (number): Overall AI detection score
• perplexityScore (number): Perplexity analysis score
• burstinessScore (number): Burstiness analysis score

isAIGenerated(text: string): boolean

Quick check to determine if text is AI-generated.

Parameters:

• text (string): The text to analyze

Returns: Boolean indicating if the text is likely AI-generated

getConfidenceScore(text: string): number

Returns the confidence score for AI detection.

Parameters:

• text (string): The text to analyze

Returns: Number between 0 and 1 representing confidence

getPerplexityScore(text: string): number

Returns the perplexity score of the text.

Parameters:

• text (string): The text to analyze

Returns: Number representing perplexity (lower = more AI-like)

getBurstinessScore(text: string): number

Returns the burstiness score of the text.

Parameters:

• text (string): The text to analyze

Returns: Number representing burstiness (lower = more AI-like)

How It Works

This library uses multiple linguistic analysis techniques to detect AI-generated text:

• Perplexity Analysis: Measures how predictable the text is
• Burstiness Analysis: Analyzes sentence-to-sentence variation
• Vocabulary Richness: Examines word diversity and complexity
• Syntactic Complexity: Analyzes sentence structure patterns
• Semantic Coherence: Measures logical flow and consistency
• N-gram Repetition: Detects repetitive patterns common in AI text
• Transition Word Usage: Analyzes overuse of connecting words
• Formality Index: Measures writing formality level
• Contextual Consistency: Checks for contextual coherence

Performance

• Bundle Size: ~15KB minified
• Zero Dependencies: No external libraries required
• Fast Processing: Analyzes typical documents in <10ms
• Memory Efficient: Minimal memory footprint

Browser Support

• Chrome 60+
• Firefox 55+
• Safari 12+
• Edge 79+
• Node.js 14+

The library analyzes various linguistic patterns commonly found in AI-generated text:

1. Sentence Structure: AI text often has consistent sentence lengths and patterns
2. Transition Words: Heavy use of formal transition words (furthermore, moreover, etc.)
3. Formality Level: AI tends to use more formal vocabulary
4. Repetitive Patterns: Common phrases and structures used by AI models
5. Passive Voice: Balanced usage patterns typical of AI optimization
6. Complexity Analysis: Word length and complexity patterns

Accuracy Notes

• This library uses heuristic analysis and pattern matching
• It's designed to catch common AI writing patterns but may not detect all AI-generated content
• Results should be used as a guide rather than definitive proof
• Accuracy may vary depending on the AI model that generated the text
• Human-written text with formal writing styles might sometimes trigger false positives

Contributing

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

License

MIT License - see LICENSE file for details.

Changelog

1.0.0

• Initial release
• Basic AI text detection functionality
• Support for Node.js and browser environments
• TypeScript support