planModel | R Documentation |
This model was pre-trained on 5,172 examples of pre-course plans from online courses at HarvardX. Each plan was annotated by research assistants for concreteness, and this model simulates those annotations on new plans.
Model pre-trained on planning data.
planModel
planModel(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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