extract_terms

<p>output from the cluster() function</p>

object

<p>Extracts terms and term frequencies</p>

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.

Alex Lishinski

extract_terms: Extracts terms and term frequencies

Description

Usage

Arguments

Details