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 | Other |
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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