adviceModel | R Documentation |
This model was pre-trained on 3289 examples of feedback on different tasks (e.g. writing a cover letter, boggle, workplace annual reviews). All of those documents were annotated by research assistants for concreteness, and this model simulates those annotations on new documents.
Model pre-trained on advice data.
adviceModel
adviceModel(texts, num.mc.cores = 1)
texts |
character A vector of texts, each of which will be tallied for concreteness. |
num.mc.cores |
numeric number of cores for parallel processing - see parallel::detectCores(). Default is 1. |
A pre-trained glmnet model
numeric Vector of concreteness ratings.
Yeomans (2020). A Concrete Application of Open Science for Natural Language Processing.
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