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Beautiful Soup

Gensim

  • Description: A robust semantic modeling library, useful for unsupervised topic modeling and natural language processing.

  • Use Case: Analyzing historical texts and documents to uncover thematic structures and trends over time.

  • GitHub Repository: Gensim GitHubarrow-up-right

Matplotlib

NetworkX

  • Description: A Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks.

  • Use Case: Modeling historical events and relationships, such as social networks, trade routes, or communication networks in historical contexts.

NLTK (Natural Language Toolkit)

  • Description: A leading platform for building Python programs to work with human language data.

  • Use Case: Text analysis and linguistic study of historical documents, including language evolution, stylistic changes, and content analysis.

  • GitHub Repository: NLTK GitHubarrow-up-right

NumPy

OCRmyPDF

  • Description: Adds an OCR text layer to PDF files, allowing them to be searched.

  • Use Case: Converting scanned historical documents and texts into searchable and analyzable PDF formats.

Pandas

Plotly

spaCy

  • Description: An open-source software library for advanced natural language processing.

  • Use Case: Processing and analyzing large volumes of historical texts for semantic content, named entity recognition, and thematic analysis.

  • GitHub Repository: spaCy GitHubarrow-up-right

TextBlob

  • Description: A library for processing textual data, providing simple APIs for common natural language processing tasks.

  • Use Case: Sentiment analysis, part-of-speech tagging, and classification of historical narratives and documents.

Tesseract OCR

  • Description: An optical character recognition (OCR) engine.

  • Use Case: Extracting text from images of historical documents, enabling digitization and analysis of archival materials.


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