teacher_rate

A data set containing almost 3,800 student ratings and written comments
regarding instructor quality along with the students' grades associated with
the course.

datasets

Provides text mining methods for social science research. The
package implements estimation, inference, summarization, and goodness-of-fit
methods for topic models including Latent Dirichlet Allocation (LDA),
supervised LDA, and supervised LDA with covariates using Bayesian Markov Chain
Monte Carlo. A description of the key models and estimation methods is available
in Wilcox, Jacobucci, Zhang, & Ammerman (2021). <doi:10.31234/osf.io/62tc3>.

Kenneth Wilcox

psychtm

Text Mining Methods for Psychological Research

teacher_rate function

A data frame with 3,733 rows and 4 variables:<dl class="dl-horizontal">
<dt>id</dt><dd>Row number to identify rater</dd>
<dt>rating</dt><dd>A numerical rating of instructor quality
from 1 (worst) to 5 (best)</dd>
<dt>grade</dt><dd>A numerical grade received by the rater for the instructor's
course ranging from 1 (worst) to 13 (best)</dd>
<dt>doc</dt><dd>A character vector containing pseudo-written comments about the
instructors</dd>
</dl>

Format

Synthetic (fake) student ratings of instructor quality. — teacher_rate

A data frame with 3,733 rows and 4 variables:<dl class='dl-horizontal'>
<dt>id</dt><dd>Row number to identify rater</dd>
<dt>rating</dt><dd>A numerical rating of instructor quality
from 1 (worst) to 5 (best)</dd>
<dt>grade</dt><dd>A numerical grade received by the rater for the instructor's
course ranging from 1 (worst) to 13 (best)</dd>
<dt>doc</dt><dd>A character vector containing pseudo-written comments about the
instructors</dd>
</dl>

teacher_rate: Synthetic (fake) student ratings of instructor quality.

Description

Usage

Arguments

Format