CDU-data-science-team/experienceAnalysis: Helper Functions for Text Mining

Package `{experienceAnalysis}` contains a suite of functions for performing _text mining_ such as sentiment analysis, analysis of word counts, TF-IDFs and _n_-grams etc. The package was developed as a helper package for use with other packages/repos developed by the [CDU Data Science Team](https://github.com/CDU-data-science-team), but the functions are generic and thus suitable for broader use. The largest focus is on calculating sentiment indicators and word counts/frequencies for labeled or unlabeled text, and plotting the outcomes to easily detect potentially important information in the text. However, there are a few "spin-off" functions for assessing the performance of a classification model, e.g. calculating accuracy per class, making and plotting confusion matrices etc.\n The package makes extensive use of [{tidytext}](https://www.tidytextmining.com/index.html) (Silge & Robinson, 2017) but also employs `Python` libraries for sentiment analysis (e.g. [TextBlob](https://textblob.readthedocs.io/en/dev/)) with the use of [{reticulate}](https://rstudio.github.io/reticulate/).

install.packages("remotes")
remotes::install_github("CDU-data-science-team/experienceAnalysis")