politeness (version 0.9.4)

politenessModel: Pre-Trained Politeness Classifier

Description

Pre-trained model to detect politeness based on data from Danescu-Niculescu-Mizil et al. (2013)

Usage

politenessModel(texts, num_mc_cores = 1)

Value

a vector with receptiveness scores

Arguments

texts

character A vector of texts, each of which will be given a politeness score.

num_mc_cores

integer Number of cores for parallelization.

Details

This is a wrapper around a pre-trained model of "politeness" for all the data from the 2013 DNM et al paper. This model requires grammar parsing via SpaCy. Please see spacyr for details on installation.

References

Danescu-Niculescu-Mizil, C., Sudhof, M., Jurafsky, D., Leskovec, J. & Potts, C. (2013). A computational approach to politeness with application to social factors. Proc. 51st ACL, 250-259.

Examples

if (FALSE) {
data("phone_offers")

politenessModel(phone_offers$message)

}