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plot.featureAssociations: visualize feature associations.ntextHits: S3 plot for contextHits class.melt_quanteda_dict: Convert a quanteda dictionary to a long data.table format.get_stopwords: Get a character vector of stopwords.get_kwic: Get keyword-in-context (KWIC) strings.get_global_i: Compute global feature positions.get_dtm: Create a document term matrix.freq_filter: Support function for subset method.feature_associations: Get common nearby features given a query or query hits.

export_span_annotations: Export span annotations.dtm_wordcloud: Plot a word cloud from a dtm.dtm_compare: Compare two document term matrices.docfreq_filter: Support function for subset method.count_tcorpus: Count results of search hits, or of a given feature in tokens.corenlp_tokens: coreNLP example sentences.compare_subset: Compare vocabulary of a subset of a tCorpus to the rest of.compare_documents: Calculate the similarity of documents.compare_corpus: Compare tCorpus vocabulary to that of another (reference).calc_chi2: Vectorized computation of chi^2 statistic for a 2x2 crosstab.

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browse_texts: Create and view a full text browser.

backbone_filter: Extract the backbone of a network.

as.tcorpus.tCorpus: Force an object to be a tCorpus class.

as.fault: Force an object to be a tCorpus class.

as.tcorpus: Force an object to be a tCorpus class.

aggregate_rsyntax: Aggregate rsyntax annotations.

agg_label: Helper function for aggregate_rsyntax.

add_multitoken_label: Choose and add multitoken strings based on multitoken.