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Calculate Lexical Dispersion

Source: R/lexical_analysis.R
calculate_lexical_dispersion.Rd

Computes lexical dispersion data for specified terms across a corpus. Shows where terms appear within each document, useful for understanding term distribution patterns.

Usage

calculate_lexical_dispersion(
  tokens_object,
  terms,
  scale = c("relative", "absolute")
)

Arguments

tokens_object

A quanteda tokens object

terms

Character vector of terms to analyze

scale

Character, "relative" (0-1 normalized) or "absolute" (token position)

Value

Data frame with columns:

  • doc_id: Document identifier

  • term: The search term

  • position: Position in document (relative or absolute)

  • doc_length: Total tokens in document

See also

Other lexical: calculate_dispersion_metrics(), 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()

Examples

if (FALSE) { # \dontrun{
library(quanteda)
toks <- tokens(c("The cat sat on the mat", "The dog ran in the park"))
dispersion <- calculate_lexical_dispersion(toks, c("the", "cat", "dog"))
} # }