Politeness is a universal dimension of langauge (Lakoff, 1973; Brown & Levinson, 1987). In practically all communication, a speaker can choose to be more or less polite to their audience. In this package, we provide tools for researchers to measure the markers and effects of politeness in natural language.
You can install politeness directly, like so:
install.packages("politeness")Many of the politeness features containted in this package use dependency parsing. We rely on the popular python library SpaCy, which is simple to install, although the procedure can vary for different machines. Our software depends on a convenient wrapper function, spacyr, that also includes several intallation tools. If you do not have SpaCy installed, a reduced set of features is provided (i.e. those that do not require dependency tags) but this only recommended for initial tests, rather than final analyses.
Please confirm that your machine can run SpaCy and spacyr first! This step can be difficult for some machines, and we defer to the existing documentation for that software as a guide. Users may also want to consider RStudio Cloud, which can support all of this software without local installation issues.
In the package we have included a dataset, phone_offers. It was
collected from an experiment in which participants were told to write
offers asking to buy a smartphone from a seller on Craigslist. We
randomly manipulated their instructions so that their task was to write
in a warm or tough style. The dataset includes the text of their
messages, as well as the condition assignment.
data("phone_offers")
politeness::politeness(phone_offers$message)
# install.packages("spacyr")
#spacyr::spacy_initialize(python_executable = "PYTHON_PATH")
#politeness::politeness(phone_offers$message, parser="spacy")
politeness::politenessPlot(politeness::politeness(phone_offers$message),
split=phone_offers$condition,
split_levels = c("Warm","Tough"),
split_name = "Condition")