Homer, a text analyser in Python, can help make your text more clear, simple and useful for your readers.

A Modern C++ Data Sciences Toolkit

Natural language detection library for Rust. Try demo online: https://whatlang.org/

Repository with all what is necessary for sentiment analysis and related areas

PHP Text Analysis is a library for performing Information Retrieval (IR) and Natural Language Processing (NLP) tasks using the PHP language

Open Source research tool to search, browse, analyze and explore large document collections by Semantic Search Engine and Open Source Text Mining & Text Analytics platform (Integrates ETL for document processing, OCR for images & PDF, named entity recognition for persons, organizations & locations, metadata management by thesaurus & ontologies, search user interface & search apps for fulltext search, faceted search & knowledge graph)

Jekyll-based static site for The Programming Historian

Resources for learning about Text Mining and Natural Language Processing

Tutorial and introduction into programming with Python for the humanities and social sciences

🗣️ Tool to generate adversarial text examples and test machine learning models against them

Language, Knowledge, Cognition

Extraction of the journalistic five W and one H questions (5W1H) from news articles: who did what, when, where, why, and how?

Textpipe: clean and extract metadata from text

✊ Detect non-inclusive language in your source code.

Interpretable data visualizations for understanding how texts differ at the word level

Fake News Detection in Python

Text vectorization tool to outperform TFIDF for classification tasks

Tools for cleaning and normalizing text data

Obsei is intended to be an automation tool for text analysis need.

A simple WikiText parsing library for MediaWiki

Awesome-Text-Classification Projects,Papers,Tutorial .

Code and Resources for "Applied Machine Learning"

Quantitative Discourse Analysis Package: Bridging the gap between qualitative data and quantitative analysis

Manuscript of the book "Supervised Machine Learning for Text Analysis in R" by Emil Hvitfeldt and Julia Silge

Stanford NLP group's shared Python tools.

This case study shows how to create a model for text analysis and classification and deploy it as a web service in Azure cloud in order to automatically classify support tickets. This project is a proof of concept made by Microsoft (Commercial Software Engineering team) in collaboration with Endava http://endava.com/en

A neural network intent parser

The repository provides usefull python scripts for ML and data analysis

A text analysis application for performing common NLP tasks through a web dashboard interface and an API