planModel {doc2concrete}R Documentation

Pre-trained Concreteness Detection Model for Plan-Making

Description

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.

Usage

planModel

planModel(texts, num.mc.cores = 1)

Arguments

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.

Format

A pre-trained glmnet model

Value

numeric Vector of concreteness ratings.

Source

Yeomans (2020). A Concrete Application of Open Science for Natural Language Processing.


[Package doc2concrete version 0.6.0 Index]