Get Topic Prevalence (Gamma) from STM Model

Extracts topic prevalence values (gamma/theta) from a fitted STM model, returning mean prevalence for each topic as a data frame.

Usage

get_topic_prevalence(stm_model, category = NULL, include_theta = FALSE)

Arguments

stm_model

A fitted STM model object from stm::stm().

category

Optional character string to add as a category column.

include_theta

Logical, if TRUE includes document-topic matrix (default: FALSE).

Value

A data frame with columns:

topic

Topic number

gamma

Mean topic prevalence across documents

category

Category label (if provided)

See also

Other topic-modeling: analyze_semantic_evolution(), assess_hybrid_stability(), calculate_assignment_consistency(), calculate_eval_metrics_internal(), calculate_keyword_stability(), calculate_semantic_drift(), calculate_topic_probability(), calculate_topic_stability(), find_optimal_k(), find_topic_matches(), fit_embedding_topics(), fit_hybrid_model(), fit_temporal_model(), generate_topic_labels(), get_topic_terms(), get_topic_texts(), identify_topic_trends(), plot_model_comparison(), plot_quality_metrics(), run_contrastive_topics_internal(), run_neural_topics_internal(), run_temporal_topics_internal(), validate_semantic_coherence()

Examples

if (FALSE) { # \dontrun{
# Fit STM model
topic_model <- stm::stm(documents, vocab, K = 10)

# Get topic prevalence
prevalence <- get_topic_prevalence(topic_model)

# With category label
prevalence_sld <- get_topic_prevalence(topic_model, category = "SLD")
} # }