The Text Analysis Suite is a collection of Python modules designed to analyze text for various linguistic attributes. This suite provides insights into the complexity, diversity, and authorship likelihood of a given text.
- Authorship Detection: Detects the likelihood of a text being AI-generated based on specific algorithms.
- Language Complexity Analysis: Evaluates the complexity of the language used in the text by calculating average word length.
- Vocabulary Diversity Analysis: Measures the diversity of the vocabulary by calculating the unique word ratio.
authorship_detection.py: Detects AI authorship likelihoodlanguage_analysis.py: Analyzes language complexityvocabulary_analysis.py: Analyzes vocabulary diversityanalyze_text.py: Integrates all analysis modulesREADME.md: Documentation for the suite
To detect whether a text is likely AI-generated:
from authorship_detection import detect_authorship
text = "Your input text here"
authorship_info = detect_authorship(text)
print(authorship_info)To analyze the language complexity of a text:
from language_analysis import analyze_language_complexity
text = "Your input text here"
language_info = analyze_language_complexity(text)
print(language_info)To analyze the vocabulary diversity of a text:
from vocabulary_analysis import analyze_vocabulary_diversity
text = "Your input text here"
vocabulary_info = analyze_vocabulary_diversity(text)
print(vocabulary_info)To perform a combined analysis of authorship, language complexity, and vocabulary diversity:
from analyze_text import analyze_text, output_metadata
text = "Your input text here"
analysis_results = analyze_text(text)
output_metadata(analysis_results)Clone the repository and navigate to the directory:
git clone https://github.com/your-repo-url/text-analysis-suite.git
cd text-analysis-suiteThis project is licensed under the MIT License - see the LICENSE.md file for details.
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