assemble_corpus

The data from which the corpus is drawn with documents in
first column

data

Words to exclude from the clustering

stopwords

Whether to remove text associated with Twitter content, useful for when analyzing data from this source (defaults to FALSE)

remove_twitter

The metadata columns following the text column

Provides an interface to perform cluster analysis on a corpus of
text. Interfaces to Quanteda to assemble text corpuses easily. Deviationalizes
text vectors prior to clustering using technique described by Sherin (Sherin,
B. [2013]. A computational study of commonsense science: An exploration in the
automated analysis of clinical interview data. Journal of the Learning Sciences,
22(4), 600-638. Chicago. <doi:10.1080/10508406.2013.836654>). Uses
cosine similarity as distance metric for two stage clustering process, involving
Ward's algorithm hierarchical agglomerative clustering, and k-means clustering.
Selects optimal number of clusters to maximize "variance explained" by clusters,
adjusted by the number of clusters. Provides plotted output of clustering
results as well as printed output. Assesses "model fit" of clustering solution
to a set of preexisting groups in dataset.

assemble_corpus: First corpus building function

Description

Usage

Arguments

Details