% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/topic_modeling.R
\name{calculate_topic_diversity}
\alias{calculate_topic_diversity}
\title{Calculate Topic Diversity (Unique-Word Proportion)}
\usage{
calculate_topic_diversity(top_terms_list, top_k = 25)
}
\arguments{
\item{top_terms_list}{Named or unnamed list of character vectors, one per topic.}

\item{top_k}{Number of top terms per topic to include (default 25).}
}
\value{
Numeric between 0 and 1, or NA if input empty.
}
\description{
Diversity = unique top-K terms across all topics / (n_topics * top_k).
Range 0 (all topics identical) to 1 (fully disjoint). Complementary to NPMI
coherence: a good model scores high on both.
}
\concept{topic-modeling}
\keyword{internal}
