clean_dfm

A corpus object as created by <code>assemble_corpus</code>.

corp

Minimum number of occurances for a term to be used

minimum_term_frequency

Minimum number of terms for document to be used

min_terms

Cleans the DFM based on specified term minimums

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.

clean_dfm: Cleans the DFM based on specified term minimums

Description

Usage

Arguments

Details