Package-level |
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An R package for the quantitative analysis of textual data |
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Get or set package options for quanteda |
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DataBuilt-in data objects. |
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A paragraph of text for testing various text-based functions |
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Immigration-related sections of 2010 UK party manifestos |
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Confidence debate from 1991 Irish Parliament |
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US presidential inaugural address texts |
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Irish budget speeches from 2010 |
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dfm from data in Table 1 of Laver, Benoit, and Garry (2003) |
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Lexicoder Sentiment Dictionary (2015) |
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Corpus functionsFunctions for constructing and manipulating corpus class objects. |
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Recast the document units of a corpus |
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Randomly sample documents from a corpus |
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Segment texts on a pattern match |
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Extract a subset of a corpus |
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Construct a corpus object |
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Get or set document-level variables |
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Return the first or last part of a corpus |
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Get or set corpus metadata |
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Get or set document-level meta-data |
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Get or assign corpus texts |
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Coerce a compressed corpus to a standard corpus |
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Tokens functionsFunctions for constructing and manipulating tokens class objects. |
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Tokenize a set of texts |
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Convert token sequences into compound tokens |
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Apply a dictionary to a tokens object |
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Create ngrams and skipgrams from tokens |
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Select or remove tokens from a tokens object |
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Replace types in tokens object |
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Extract a subset of a tokens |
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Convert the case of tokens |
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Stem the terms in an object |
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Get word types from a tokens object |
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Coercion, checking, and combining functions for tokens objects |
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Character functionsFunctions for constructing and manipulating character objects. |
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Convert the case of character objects |
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Segment texts on a pattern match |
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Create ngrams and skipgrams from tokens |
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Stem the terms in an object |
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Text matrix functionsFunctions for constructing and manipulating a document-feature matrix (dfm) or feature co-occurrence matrix object. |
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Create a document-feature matrix |
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Recombine a dfm or fcm by combining identical dimension elements |
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Combine documents in a dfm by a grouping variable |
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Apply a dictionary to a dfm |
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Randomly sample documents or features from a dfm |
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Select features from a dfm or fcm |
Replace features in dfm |
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Extract a subset of a dfm |
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Sort a dfm by frequency of one or more margins |
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Weight a dfm by tf-idf |
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Convert the case of the features of a dfm and combine |
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Trim a dfm using frequency threshold-based feature selection |
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Weight the feature frequencies in a dfm |
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Stem the terms in an object |
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Compute the (weighted) document frequency of a feature |
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Return the first or last part of a dfm |
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Coercion and checking functions for dfm objects |
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Coerce a dfm to a matrix or data.frame |
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Create a feature co-occurrence matrix |
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Sort an fcm in alphabetical order of the features |
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Text StatisticsFunctions for computing statistics from texts and dfm objects. |
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Identify and score multi-word expressions |
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Similarity and distance computation between documents or features |
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Calculate lexical diversity |
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Tabulate feature frequencies |
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Calculate keyness statistics |
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Calculate readability |
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Compute the sparsity of a document-feature matrix |
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Identify the most frequent features in a dfm |
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Dictionary functionsConstructor and utility functions for working with dictionaries. |
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Create a dictionary |
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Coercion and checking functions for dictionary objects |
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Convert quanteda dictionary objects to the YAML format |
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Phrase discovery functionsFunctions for exploring and detecting keywords and phrases. |
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Identify and score multi-word expressions |
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Locate keywords-in-context |
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Text plot functionsPlot functions for representing text and the analysis of texts. |
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Influence plot for text scaling models |
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Plot word keyness |
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Plot a network of feature co-occurrences |
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Plot a fitted scaling model |
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Plot features as a wordcloud |
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Plot the dispersion of key word(s) |
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Text Model FunctionsPlot functions for fitting analytic models from text matrixes. |
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Class affinity maximum likelihood text scaling model |
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Correspondence analysis of a document-feature matrix |
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Latent Semantic Analysis |
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Naive Bayes classifier for texts |
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Wordfish text model |
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Wordscores text model |
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Utility functionsR-like functions to return counts and object information. |
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Count the number of documents or features |
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Count the Scrabble letter values of text |
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Count the number of sentences |
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Count syllables in a text |
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Count the number of tokens or types |
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Get or set document names |
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Get the feature labels from a dfm |
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Miscellaneous functions |
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Declare a compound character to be a sequence of separate pattern matches |
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Coerce a dist object into a list |
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Convert a dfm to a non-quanteda format |
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Bootstrap a dfm |
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Extensions for and from spacy_parse objects |