Text Classifier: AI vs SLW (Second Language Writers)

This project was built as a personal learning project to explore linguistic data science, and syntactic complexity modeling.

Live App

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Features

• Load real-world .txt samples by index
• Visualize Syntactic Complexity Indices (e.g., MLS, CN_C, VP_T)
• Generate classification results with confidence scores
• Explore SHAP waterfall plots to interpret predictions

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About the syntactic Complexity Indices

The classifier uses L2SCA Indices by TAASSC

Predictions are supported by SHAP contribution plots, showing how each feature influences the outcome toward AI or SLW.

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Data Overview

The dataset consists of 300 text samples divided into three categories:

• 1–100: Human-written texts by second language writers (SLW)
• 101–200: AI-generated texts using general prompts
• 201–300: AI-generated texts created by prompting large language models (LLMs) to mimic SLW writing style

Data prepocessing by TAASSC

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Data Usage Notice

• The .txt files in txt_samples/ are included only for demonstration and learning purposes.
  They are not licensed for reuse, redistribution, or commercial use.
  See txt_samples/LICENSE.txt for full terms.

• The dataset file X_binary.csv is private and is not licensed for reuse, redistribution, or modification.
  It is shared solely for demonstration purposes and should not be used for any other purpose.

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License

This project's code is licensed under the MIT License.