An R package for the Quantitative Analysis of Textual Data
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Updated
May 7, 2024 - R
Natural language processing (NLP) is a field of computer science that studies how computers and humans interact. In the 1950s, Alan Turing published an article that proposed a measure of intelligence, now called the Turing test. More modern techniques, such as deep learning, have produced results in the fields of language modeling, parsing, and natural-language tasks.
An R package for the Quantitative Analysis of Textual Data
Text mining using tidy tools ✨📄✨
Fast vectorization, topic modeling, distances and GloVe word embeddings in R.
R package providing annotators and a normalized data model for natural language processing
Implementation of BERT in R
performing sentiment analysis on the whatsapp chats.
A Shiny Application for Inspecting Structural Topic Models
An R package for Keyword Assisted Topic Models
R package for Ripple Down Rules-based Part-Of-Speech Tagging (RDRPOS). On more than 45 languages.
Summarise text by finding relevant sentences and keywords using the Textrank algorithm
R client binding for the Rosette API
R Shiny app for tweet analysis
Visualization tools to use with RBERT
Contextualised Embeddings and Language Modelling using BERT and Friends using R
Applying unsupervised learning using K-means clustering.
Document similarity using cosine distance, tf-idf, and latent semantic analysis.
DEPRECATED - The Concept Mover's Distance Method is now available in the text2map package. Concept Mover's Distance is a way to measure a document's conceptual engagement using word embeddings.
IBM Watson Natural Language Understanding API Wrapper package for R
Classify messages as Spam or Ham using a simple Naive bayes classifier. After training the Model , next deployment of a web app build on shiny to filter text messages.
Detect UN Sustainable Development Goals in Text
Created by Alan Turing