wzf9 / akc

Automatic knowledge classification based on keyword co-occurrrence network

akc: Automatic knowledge classification

Short for automatic knowledge classification, akc is an R package used to carry out keyword classification based on network science (mainly community detection techniques), using bibliometric data. However, these provided functions are general, and could be extended to solve other tasks in text mining as well.

Features

Generally provides a tidy framework of data manipulation supported by dplyr, akc was written in data.table when necessary to guarantee the performance for big data analysis. Meanwhile, akc also utilizes the state-of-the-art text mining functions provided by stringr,tidytext,textstem and network analysis functions provided by igraph,tidygraph and ggraph. Pipe %>% has been exported from magrittr and could be used directly in akc.

Installation

install.packages("akc")
# or
devtools::install_github("hope-data-science/akc")

Note: As akc utilizes many state-of-the-art functions from various excellent R packages, it might take a while to install the whole suite, especially when you are still not a heavy R user (then lots of packages might not be installed in advance). Nevertheless, the patience pays off. The well-organized framework will save you much more time afterward.

TODO

More layouts for the network, utilizing graphlayouts, etc.

Further information

See vignette and tutorial .