
Using tidy data principles can make many text mining tasks easier, more effective, and consistent with tools already in wide use. Much of the infrastructure needed for text mining with tidy data frames already exists in packages like 'dplyr', 'broom', 'tidyr', and 'ggplot2'. In this package, we provide functions and supporting data sets to allow conversion of text to and from tidy formats, and to switch seamlessly between tidy tools and existing text mining packages.
Maintainer: Julia Silge [email protected] (ORCID)
Authors:
David Robinson [email protected]
Other contributors:
Gabriela De Queiroz [email protected] [contributor]
Colin Fay [email protected] (ORCID) [contributor]
Emil Hvitfeldt [email protected] [contributor]
Os Keyes [email protected] (ORCID) [contributor]
Kanishka Misra [email protected] [contributor]
Tim Mastny [email protected] [contributor]
Jeff Erickson [email protected] [contributor]
Useful links: