quanteda: An R package for the quantitative analysis of textual data

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Authors Kenneth Benoit, Kohei Watanabe, +4 authors Akitaka Matsuo
Journal/Conference Name J. Open Source Software
Paper Category
Paper Abstract quanteda is an R package providing a comprehensive workflow and toolkit for natural language processing tasks such as corpus management, tokenization, analysis, and visualization. It has extensive functions for applying dictionary analysis, exploring texts using keywords-in-context, computing document and feature similarities, and discovering multi-word expressions through collocation scoring. Based entirely on sparse operations, it provides highly efficient methods for compiling document-feature matrices and for manipulating these or using them in further quantitative analysis. Using C++ and multithreading extensively, quanteda is also considerably faster and more efficient than other R and Python packages in processing large textual data.
Date of publication 2018
Code Programming Language R

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