featureSet {DICEM} | R Documentation |
Extracts feature sets to match pre-trained models
featureSet(text, parser = c("none", "spacy"), num_mc_cores = 1)
text |
character A vector of texts, each of which will be tallied for politeness features. |
parser |
character Name of dependency parser to use (see details). Without a dependency parser, the politeness features are excluded from the model. |
num_mc_cores |
integer Number of cores for parallelization. Default is 1, but we encourage users to try parallel::detectCores() if possible. |
The politeness features depend on part-of-speech tagged sentences (e.g. "bare commands" are a particular verb class). To include these features in the analysis, a POS tagger must be initialized beforehand - we currently support SpaCy which must be installed separately in Python (see example for implementation).
a data.frame of features, matching the pre-trained model set