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    },
    {
      "version": "1.3.0",
      "date": "2018-06-05"
    },
    {
      "version": "1.3.4",
      "date": "2018-07-15"
    },
    {
      "version": "1.3.13",
      "date": "2018-11-01"
    },
    {
      "version": "1.3.14",
      "date": "2018-11-19"
    },
    {
      "version": "1.4.0",
      "date": "2019-01-30"
    },
    {
      "version": "1.4.1",
      "date": "2019-02-26"
    },
    {
      "version": "1.4.3",
      "date": "2019-04-01"
    },
    {
      "version": "1.5.0",
      "date": "2019-07-04"
    },
    {
      "version": "1.5.1",
      "date": "2019-07-30"
    },
    {
      "version": "1.5.2",
      "date": "2019-11-26"
    },
    {
      "version": "2.0.0",
      "date": "2020-02-26"
    },
    {
      "version": "2.0.1",
      "date": "2020-03-18"
    },
    {
      "version": "2.1.0",
      "date": "2020-07-05"
    },
    {
      "version": "2.1.1",
      "date": "2020-07-27"
    },
    {
      "version": "2.1.2",
      "date": "2020-09-23"
    },
    {
      "version": "3.0.0",
      "date": "2021-04-06"
    },
    {
      "version": "3.1.0",
      "date": "2021-08-17"
    },
    {
      "version": "3.2.0",
      "date": "2021-11-30"
    },
    {
      "version": "3.2.1",
      "date": "2022-03-01"
    },
    {
      "version": "3.2.2",
      "date": "2022-08-09"
    },
    {
      "version": "3.2.3",
      "date": "2022-08-29"
    },
    {
      "version": "3.2.4",
      "date": "2022-12-08"
    },
    {
      "version": "3.3.0",
      "date": "2023-04-07"
    },
    {
      "version": "3.3.1",
      "date": "2023-05-18"
    },
    {
      "version": "4.0.0",
      "date": "2024-04-04"
    },
    {
      "version": "4.0.1",
      "date": "2024-04-08"
    },
    {
      "version": "4.0.2",
      "date": "2024-04-24"
    },
    {
      "version": "4.1.0",
      "date": "2024-09-04"
    },
    {
      "version": "4.2.0",
      "date": "2025-01-08"
    },
    {
      "version": "4.3.0",
      "date": "2025-05-20"
    },
    {
      "version": "4.3.1",
      "date": "2025-07-10"
    },
    {
      "version": "4.4",
      "date": "2026-04-06"
    },
    {
      "version": "4.5.0",
      "date": "2026-08-04"
    }
  ],
  "_exports": [
    "%>%",
    "as.corpus",
    "as.dfm",
    "as.dictionary",
    "as.fcm",
    "as.list",
    "as.phrase",
    "as.tensor",
    "as.tokens",
    "as.tokens_xptr",
    "as.yaml",
    "bootstrap_dfm",
    "breakrules_get",
    "breakrules_reset",
    "breakrules_set",
    "char_keep",
    "char_ngrams",
    "char_remove",
    "char_segment",
    "char_select",
    "char_tolower",
    "char_toupper",
    "char_trim",
    "char_wordstem",
    "check_character",
    "check_double",
    "check_integer",
    "check_logical",
    "colMeans",
    "colSums",
    "Compare",
    "concat",
    "concatenator",
    "convert",
    "corpus",
    "corpus_chunk",
    "corpus_group",
    "corpus_reshape",
    "corpus_sample",
    "corpus_segment",
    "corpus_subset",
    "corpus_trim",
    "dfm",
    "dfm_compress",
    "dfm_group",
    "dfm_keep",
    "dfm_lookup",
    "dfm_match",
    "dfm_remove",
    "dfm_replace",
    "dfm_sample",
    "dfm_select",
    "dfm_smooth",
    "dfm_sort",
    "dfm_subset",
    "dfm_tfidf",
    "dfm_tolower",
    "dfm_toupper",
    "dfm_trim",
    "dfm_weight",
    "dfm_wordstem",
    "dictionary",
    "docfreq",
    "docid",
    "docnames",
    "docnames<-",
    "docvars",
    "docvars<-",
    "drop0",
    "fcm",
    "fcm_compress",
    "fcm_keep",
    "fcm_remove",
    "fcm_select",
    "fcm_sort",
    "fcm_tolower",
    "fcm_toupper",
    "featfreq",
    "featnames",
    "flatten_dictionary",
    "index",
    "info_tbb",
    "is.collocations",
    "is.corpus",
    "is.dfm",
    "is.dictionary",
    "is.fcm",
    "is.index",
    "is.kwic",
    "is.phrase",
    "is.tokens",
    "is.tokens_xptr",
    "kwic",
    "meta",
    "meta<-",
    "ndoc",
    "nfeat",
    "normalize_characters",
    "nsentence",
    "ntoken",
    "ntype",
    "object2fixed",
    "object2id",
    "pattern2fixed",
    "pattern2id",
    "phrase",
    "print",
    "quanteda_options",
    "rowMeans",
    "rownames<-",
    "rowSums",
    "segid",
    "sparsity",
    "stopwords",
    "t",
    "texts",
    "texts<-",
    "tokenize_character",
    "tokenize_custom",
    "tokenize_dictionary",
    "tokenize_fasterword",
    "tokenize_fastestword",
    "tokenize_paragraph",
    "tokenize_sentence",
    "tokenize_word1",
    "tokenize_word2",
    "tokenize_word3",
    "tokenize_word4",
    "tokens",
    "tokens_annotate",
    "tokens_chunk",
    "tokens_compound",
    "tokens_group",
    "tokens_keep",
    "tokens_lookup",
    "tokens_match",
    "tokens_ngrams",
    "tokens_recompile",
    "tokens_remove",
    "tokens_replace",
    "tokens_restore",
    "tokens_sample",
    "tokens_segment",
    "tokens_select",
    "tokens_skipgrams",
    "tokens_split",
    "tokens_subset",
    "tokens_tolower",
    "tokens_toupper",
    "tokens_trim",
    "tokens_wordstem",
    "topfeatures",
    "types"
  ],
  "_datasets": [
    {
      "name": "data_char_sampletext",
      "title": "A paragraph of text for testing various text-based functions",
      "object": "data_char_sampletext",
      "class": [
        "character"
      ],
      "fields": [],
      "table": false,
      "tojson": true
    },
    {
      "name": "data_char_ukimmig2010",
      "title": "Immigration-related sections of 2010 UK party manifestos",
      "object": "data_char_ukimmig2010",
      "class": [
        "character"
      ],
      "fields": [],
      "table": false,
      "tojson": true
    },
    {
      "name": "data_corpus_inaugural",
      "title": "US presidential inaugural address texts",
      "object": "data_corpus_inaugural",
      "class": [
        "corpus",
        "character"
      ],
      "fields": [],
      "table": false,
      "tojson": true
    },
    {
      "name": "data_dfm_lbgexample",
      "title": "dfm from data in Table 1 of Laver, Benoit, and Garry (2003)",
      "object": "data_dfm_lbgexample",
      "class": [
        "dfm"
      ],
      "fields": [],
      "table": false,
      "tojson": false
    },
    {
      "name": "data_dictionary_LSD2015",
      "title": "Lexicoder Sentiment Dictionary (2015)",
      "object": "data_dictionary_LSD2015",
      "class": [
        "dictionary2"
      ],
      "fields": [],
      "table": true,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "as.character.corpus",
      "title": "Coercion and checking methods for corpus objects",
      "topics": [
        "as.character.corpus",
        "as.corpus",
        "is.corpus"
      ]
    },
    {
      "page": "as.dfm",
      "title": "Coercion and checking functions for dfm objects",
      "topics": [
        "as.dfm",
        "is.dfm"
      ]
    },
    {
      "page": "as.dictionary",
      "title": "Coercion and checking functions for dictionary objects",
      "topics": [
        "as.dictionary",
        "as.dictionary.data.frame",
        "is.dictionary"
      ]
    },
    {
      "page": "as.fcm",
      "title": "Coercion and checking functions for fcm objects",
      "topics": [
        "as.fcm"
      ]
    },
    {
      "page": "as.tokens",
      "title": "Coercion, checking, and combining functions for tokens objects",
      "topics": [
        "as.character.tokens",
        "as.list.tokens",
        "as.matrix.tokens",
        "as.tensor",
        "as.tensor.tokens",
        "as.tokens",
        "as.tokens.spacyr_parsed",
        "is.tokens"
      ]
    },
    {
      "page": "as.matrix.dfm",
      "title": "Coerce a dfm to a matrix or data.frame",
      "topics": [
        "as.matrix.dfm"
      ]
    },
    {
      "page": "as.yaml",
      "title": "Convert quanteda dictionary objects to the YAML format",
      "topics": [
        "as.yaml"
      ]
    },
    {
      "page": "bootstrap_dfm",
      "title": "Bootstrap a dfm",
      "topics": [
        "bootstrap_dfm"
      ]
    },
    {
      "page": "char_select",
      "title": "Select or remove elements from a character vector",
      "topics": [
        "char_keep",
        "char_remove",
        "char_select"
      ]
    },
    {
      "page": "char_tolower",
      "title": "Convert the case of character objects",
      "topics": [
        "char_tolower",
        "char_toupper"
      ]
    },
    {
      "page": "concat",
      "title": "Return the concatenator character from an object",
      "topics": [
        "concat",
        "concatenator"
      ]
    },
    {
      "page": "convert",
      "title": "Convert quanteda objects to non-quanteda formats",
      "topics": [
        "convert",
        "convert.corpus",
        "convert.dfm"
      ]
    },
    {
      "page": "corpus",
      "title": "Construct a corpus object",
      "topics": [
        "corpus",
        "corpus.character",
        "corpus.Corpus",
        "corpus.corpus",
        "corpus.data.frame",
        "corpus.kwic"
      ]
    },
    {
      "page": "corpus_chunk",
      "title": "Segment a corpus into chunks of a given size",
      "topics": [
        "corpus_chunk"
      ]
    },
    {
      "page": "corpus_group",
      "title": "Combine documents in corpus by a grouping variable",
      "topics": [
        "corpus_group"
      ]
    },
    {
      "page": "corpus_reshape",
      "title": "Recast the document units of a corpus",
      "topics": [
        "corpus_reshape"
      ]
    },
    {
      "page": "corpus_sample",
      "title": "Randomly sample documents from a corpus",
      "topics": [
        "corpus_sample"
      ]
    },
    {
      "page": "corpus_segment",
      "title": "Segment texts on a pattern match",
      "topics": [
        "char_segment",
        "corpus_segment"
      ]
    },
    {
      "page": "corpus_subset",
      "title": "Extract a subset of a corpus",
      "topics": [
        "corpus_subset"
      ]
    },
    {
      "page": "corpus_trim",
      "title": "Remove sentences based on their token lengths or a pattern match",
      "topics": [
        "char_trim",
        "corpus_trim"
      ]
    },
    {
      "page": "data_char_sampletext",
      "title": "A paragraph of text for testing various text-based functions",
      "topics": [
        "data_char_sampletext"
      ]
    },
    {
      "page": "data_char_ukimmig2010",
      "title": "Immigration-related sections of 2010 UK party manifestos",
      "topics": [
        "data_char_ukimmig2010"
      ]
    },
    {
      "page": "data_corpus_inaugural",
      "title": "US presidential inaugural address texts",
      "topics": [
        "data_corpus_inaugural"
      ]
    },
    {
      "page": "data_dfm_lbgexample",
      "title": "dfm from data in Table 1 of Laver, Benoit, and Garry (2003)",
      "topics": [
        "data_dfm_lbgexample"
      ]
    },
    {
      "page": "data_dictionary_LSD2015",
      "title": "Lexicoder Sentiment Dictionary (2015)",
      "topics": [
        "data_dictionary_LSD2015"
      ]
    },
    {
      "page": "dfm",
      "title": "Create a document-feature matrix",
      "topics": [
        "dfm"
      ]
    },
    {
      "page": "dfm_compress",
      "title": "Recombine a dfm or fcm by combining identical dimension elements",
      "topics": [
        "dfm_compress",
        "fcm_compress"
      ]
    },
    {
      "page": "dfm_group",
      "title": "Combine documents in a dfm by a grouping variable",
      "topics": [
        "dfm_group"
      ]
    },
    {
      "page": "dfm_lookup",
      "title": "Apply a dictionary to a dfm",
      "topics": [
        "dfm_lookup"
      ]
    },
    {
      "page": "dfm_match",
      "title": "Match the dfm columns with given features",
      "topics": [
        "dfm_match"
      ]
    },
    {
      "page": "dfm_replace",
      "title": "Replace features in dfm",
      "topics": [
        "dfm_replace"
      ]
    },
    {
      "page": "dfm_sample",
      "title": "Randomly sample documents from a dfm",
      "topics": [
        "dfm_sample"
      ]
    },
    {
      "page": "dfm_select",
      "title": "Select features from a dfm or fcm",
      "topics": [
        "dfm_keep",
        "dfm_remove",
        "dfm_select",
        "fcm_keep",
        "fcm_remove",
        "fcm_select"
      ]
    },
    {
      "page": "dfm_sort",
      "title": "Sort a dfm by frequency of one or more margins",
      "topics": [
        "dfm_sort"
      ]
    },
    {
      "page": "dfm_subset",
      "title": "Extract a subset of a dfm",
      "topics": [
        "dfm_subset"
      ]
    },
    {
      "page": "dfm_tfidf",
      "title": "Weight a dfm by _tf-idf_",
      "topics": [
        "dfm_tfidf"
      ]
    },
    {
      "page": "dfm_tolower",
      "title": "Convert the case of the features of a dfm and combine",
      "topics": [
        "dfm_tolower",
        "dfm_toupper",
        "fcm_tolower",
        "fcm_toupper"
      ]
    },
    {
      "page": "dfm_trim",
      "title": "Trim a dfm using frequency threshold-based feature selection",
      "topics": [
        "dfm_trim"
      ]
    },
    {
      "page": "dfm_weight",
      "title": "Weight the feature frequencies in a dfm",
      "topics": [
        "dfm_smooth",
        "dfm_weight"
      ]
    },
    {
      "page": "dictionary",
      "title": "Create a dictionary object",
      "topics": [
        "dictionary"
      ]
    },
    {
      "page": "docfreq",
      "title": "Compute the (weighted) document frequencies of features",
      "topics": [
        "docfreq"
      ]
    },
    {
      "page": "docnames",
      "title": "Get or set document names",
      "topics": [
        "docid",
        "docnames",
        "docnames<-",
        "segid"
      ]
    },
    {
      "page": "docvars",
      "title": "Get or set document-level variables",
      "topics": [
        "$.corpus",
        "$.dfm",
        "$.tokens",
        "$<-.corpus",
        "$<-.dfm",
        "$<-.tokens",
        "docvars",
        "docvars<-"
      ]
    },
    {
      "page": "fcm",
      "title": "Create a feature co-occurrence matrix",
      "topics": [
        "fcm",
        "is.fcm"
      ]
    },
    {
      "page": "fcm_sort",
      "title": "Sort an fcm in alphabetical order of the features",
      "topics": [
        "fcm_sort"
      ]
    },
    {
      "page": "featfreq",
      "title": "Compute the frequencies of features",
      "topics": [
        "featfreq"
      ]
    },
    {
      "page": "featnames",
      "title": "Get the feature labels from a dfm",
      "topics": [
        "featnames"
      ]
    },
    {
      "page": "index",
      "title": "Locate a pattern in a tokens object",
      "topics": [
        "index",
        "is.index"
      ]
    },
    {
      "page": "is.collocations",
      "title": "Check if an object is collocations",
      "topics": [
        "is.collocations"
      ]
    },
    {
      "page": "kwic",
      "title": "Locate keywords-in-context",
      "topics": [
        "as.data.frame.kwic",
        "is.kwic",
        "kwic"
      ]
    },
    {
      "page": "meta",
      "title": "Get or set object metadata",
      "topics": [
        "meta",
        "meta<-"
      ]
    },
    {
      "page": "ndoc",
      "title": "Count the number of documents or features",
      "topics": [
        "ndoc",
        "nfeat"
      ]
    },
    {
      "page": "nsentence",
      "title": "Count the number of sentences",
      "topics": [
        "nsentence"
      ]
    },
    {
      "page": "ntoken",
      "title": "Count the number of tokens or types",
      "topics": [
        "ntoken",
        "ntype"
      ]
    },
    {
      "page": "phrase",
      "title": "Declare a pattern to be a sequence of separate patterns",
      "topics": [
        "as.phrase",
        "is.phrase",
        "phrase"
      ]
    },
    {
      "page": "print-methods",
      "title": "Print methods for quanteda core objects",
      "topics": [
        "print,dfm-method",
        "print,dictionary2-method",
        "print,fcm-method",
        "print-methods",
        "print.corpus",
        "print.dfm",
        "print.dictionary",
        "print.kwic",
        "print.tokens"
      ]
    },
    {
      "page": "quanteda_options",
      "title": "Get or set package options for quanteda",
      "topics": [
        "quanteda_options"
      ]
    },
    {
      "page": "spacyr-methods",
      "title": "Extensions for and from spacy_parse objects",
      "topics": [
        "spacyr-methods"
      ]
    },
    {
      "page": "sparsity",
      "title": "Compute the sparsity of a document-feature matrix",
      "topics": [
        "sparsity"
      ]
    },
    {
      "page": "textmodels",
      "title": "Models for scaling and classification of textual data",
      "topics": [
        "textmodels"
      ]
    },
    {
      "page": "textplots",
      "title": "Plots for textual data",
      "topics": [
        "textplots"
      ]
    },
    {
      "page": "textstats",
      "title": "Statistics for textual data",
      "topics": [
        "textstats"
      ]
    },
    {
      "page": "tokens",
      "title": "Construct a tokens object",
      "topics": [
        "tokens"
      ]
    },
    {
      "page": "tokens_annotate",
      "title": "Annotate a tokens object using a dictionary",
      "topics": [
        "tokens_annotate"
      ]
    },
    {
      "page": "tokens_chunk",
      "title": "Segment tokens object by chunks of a given size",
      "topics": [
        "tokens_chunk"
      ]
    },
    {
      "page": "tokens_compound",
      "title": "Convert token sequences into compound tokens",
      "topics": [
        "tokens_compound"
      ]
    },
    {
      "page": "tokens_group",
      "title": "Combine documents in a tokens object by a grouping variable",
      "topics": [
        "tokens_group"
      ]
    },
    {
      "page": "tokens_lookup",
      "title": "Apply a dictionary to a tokens object",
      "topics": [
        "tokens_lookup"
      ]
    },
    {
      "page": "tokens_match",
      "title": "Match the tokens IDs with given types",
      "topics": [
        "tokens_match"
      ]
    },
    {
      "page": "tokens_ngrams",
      "title": "Create n-grams and skip-grams from tokens",
      "topics": [
        "char_ngrams",
        "tokens_ngrams",
        "tokens_skipgrams"
      ]
    },
    {
      "page": "tokens_replace",
      "title": "Replace tokens in a tokens object",
      "topics": [
        "tokens_replace"
      ]
    },
    {
      "page": "tokens_sample",
      "title": "Randomly sample documents from a tokens object",
      "topics": [
        "tokens_sample"
      ]
    },
    {
      "page": "tokens_segment",
      "title": "Segment tokens object by patterns",
      "topics": [
        "tokens_segment"
      ]
    },
    {
      "page": "tokens_select",
      "title": "Select or remove tokens from a tokens object",
      "topics": [
        "tokens_keep",
        "tokens_remove",
        "tokens_select"
      ]
    },
    {
      "page": "tokens_split",
      "title": "Split tokens by a separator pattern",
      "topics": [
        "tokens_split"
      ]
    },
    {
      "page": "tokens_subset",
      "title": "Extract a subset of a tokens",
      "topics": [
        "tokens_subset"
      ]
    },
    {
      "page": "tokens_tolower",
      "title": "Convert the case of tokens",
      "topics": [
        "tokens_tolower",
        "tokens_toupper"
      ]
    },
    {
      "page": "tokens_trim",
      "title": "Trim tokens using frequency threshold-based feature selection",
      "topics": [
        "tokens_trim"
      ]
    },
    {
      "page": "tokens_wordstem",
      "title": "Stem the terms in an object",
      "topics": [
        "char_wordstem",
        "dfm_wordstem",
        "tokens_wordstem"
      ]
    },
    {
      "page": "tokens_xptr",
      "title": "Methods for tokens_xptr objects",
      "topics": [
        "as.tokens_xptr",
        "as.tokens_xptr.tokens",
        "as.tokens_xptr.tokens_xptr",
        "is.tokens_xptr",
        "tokens_xptr"
      ]
    },
    {
      "page": "topfeatures",
      "title": "Identify the most frequent features in a dfm",
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        "Additional recommended packages:",
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        "Loading in files using the readtext package",
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