Computes quantitative dispersion metrics for terms, measuring how evenly distributed they are across the corpus.
Value
Data frame with columns:
term: The search term
frequency: Total occurrences
doc_count: Number of documents containing term
doc_ratio: Proportion of documents containing term
juilland_d: Juilland's D dispersion (0-1, higher = more even)
rosengren_s: Rosengren's S dispersion
See also
Other lexical:
calculate_lexical_dispersion(),
calculate_log_odds_ratio(),
calculate_text_readability(),
clear_lexdiv_cache(),
detect_multi_words(),
extract_keywords_keyness(),
extract_keywords_tfidf(),
extract_morphology(),
extract_named_entities(),
extract_noun_chunks(),
extract_pos_tags(),
extract_subjects_objects(),
find_similar_words(),
get_sentences(),
get_spacy_embeddings(),
get_spacy_model_info(),
get_word_similarity(),
init_spacy_nlp(),
lexical_analysis,
lexical_diversity_analysis(),
lexical_frequency_analysis(),
parse_morphology_string(),
plot_keyness_keywords(),
plot_keyword_comparison(),
plot_lexical_diversity_distribution(),
plot_morphology_feature(),
plot_readability_by_group(),
plot_readability_distribution(),
plot_tfidf_keywords(),
plot_top_readability_documents(),
render_displacy_dep(),
render_displacy_ent(),
spacy_extract_entities(),
spacy_has_vectors(),
spacy_initialized(),
spacy_parse_full(),
summarize_morphology()