# Managing, Querying and Analyzing Tokenized Text

## Documentation for package ‘corpustools’ version 0.4.2

- DESCRIPTION file.
- User guides, package vignettes and other documentation.

## Help Pages

A B C D E F G L M P R S T

## -- A --

add_collocation_label | Choose and add collocation strings based on collocation categories
agg_tcorpus | Aggregate the tokens data
as.tcorpus | Force an object to be a tCorpus class
as.tcorpus.default | Force an object to be a tCorpus class
as.tcorpus.tCorpus | Force an object to be a tCorpus class

## -- B --

backbone_filter | Extract the backbone of a network.
browse_hits | View hits in a browser
browse_texts | Create and view a full text browser

## -- C --

calc_chi2 | Vectorized computation of chi^2 statistic for a 2x2 crosstab containing the values [a, b] [c, d]
code_dictionary | Dictionary lookup
code_features | Code features in a tCorpus based on a search string
compare_corpus | Compare tCorpus vocabulary to that of another (reference) tCorpus
compare_documents | Calculate the similarity of documents
compare_subset | Compare vocabulary of a subset of a tCorpus to the rest of the tCorpus
context | Get a context vector
corenlp_tokens | coreNLP example sentences
count_tcorpus | Count results of search hits, or of a given feature in tokens
create_tcorpus | Create a tCorpus
create_tcorpus.character | Create a tCorpus
create_tcorpus.corpus | Create a tCorpus
create_tcorpus.data.frame | Create a tCorpus
create_tcorpus.factor | Create a tCorpus

## -- D --

deduplicate | Deduplicate documents
delete_columns | Delete column from the data and meta data
delete_meta_columns | Delete column from the data and meta data
docfreq_filter | Support function for subset method
dtm_compare | Compare two document term matrices
dtm_wordcloud | Plot a word cloud from a dtm

## -- E --

ego_semnet | Create an ego network
emoticon_dict | Dictionary with common ASCII emoticons

## -- F --

feats_to_columms | Cast the "feats" column in UDpipe tokens to columns
feature_associations | Get common nearby features given a query or query hits
feature_stats | Feature statistics
feature_subset | Filter features
freq_filter | Support function for subset method

## -- G --

get | Access the data from a tCorpus
get_dfm | Create a document term matrix.
get_dtm | Create a document term matrix.
get_global_i | Compute global feature positions
get_kwic | Get keyword-in-context (KWIC) strings
get_meta | Access the data from a tCorpus
get_stopwords | Get a character vector of stopwords

## -- L --

laplace | Laplace (i.e. add constant) smoothing
lda_fit | Estimate a LDA topic model

## -- M --

melt_quanteda_dict | Convert a quanteda dictionary to a long data.table format
merge_tcorpora | Merge tCorpus objects

## -- P --

plot.contextHits | S3 plot for contextHits class
plot.featureAssociations | visualize feature associations
plot.featureHits | S3 plot for featureHits class
plot.vocabularyComparison | visualize vocabularyComparison
plot_semnet | Visualize a semnet network
plot_words | Plot a wordcloud with words ordered and coloured according to a dimension (x)
preprocess | Preprocess feature
preprocess_tokens | Preprocess tokens in a character vector
print.contextHits | S3 print for contextHits class
print.featureHits | S3 print for featureHits class
print.tCorpus | S3 print for tCorpus class

## -- R --

refresh_tcorpus | Refresh a tCorpus object using the current version of corpustools
replace_dictionary | Replace tokens with dictionary match
require_package | Check if package with given version exists

## -- S --

search_contexts | Search for documents or sentences using Boolean queries
search_dictionary | Dictionary lookup
search_features | Find tokens using a Lucene-like search query
search_recode | Recode features in a tCorpus based on a search string
semnet | Create a semantic network based on the co-occurence of tokens in documents
semnet_window | Create a semantic network based on the co-occurence of tokens in token windows
set | Modify the token and meta data.tables of a tCorpus
set_levels | Change levels of factor columns
set_meta | Modify the token and meta data.tables of a tCorpus
set_meta_levels | Change levels of factor columns
set_meta_name | Change column names of data and meta data
set_name | Change column names of data and meta data
set_network_attributes | Set some default network attributes for pretty plotting
set_special | Designate column as columns with special meaning (token, lemma, POS, relation, parent)
sgt | Simple Good Turing smoothing
show_udpipe_models | Show the names of udpipe models
sotu_texts | State of the Union addresses
stopwords_list | Basic stopword lists
subset | Subset a tCorpus
subset.tCorpus | S3 subset for tCorpus class
subset_meta | Subset a tCorpus
subset_query | Subset tCorpus token data using a query
summary.contextHits | S3 summary for contextHits class
summary.featureHits | S3 summary for featureHits class
summary.tCorpus | Summary of a tCorpus object

## -- T --

tCorpus | tCorpus: a corpus class for tokenized texts
tcorpus | tCorpus: a corpus class for tokenized texts
tCorpus$code_dictionary | Dictionary lookup
tCorpus$code_features | Code features in a tCorpus based on a search string
tCorpus$compare_corpus | Compare tCorpus vocabulary to that of another (reference) tCorpus
tCorpus$compare_documents | Calculate the similarity of documents
tCorpus$compare_subset | Compare vocabulary of a subset of a tCorpus to the rest of the tCorpus
tCorpus$context | Get a context vector
tCorpus$deduplicate | Deduplicate documents
tCorpus$delete_columns | Delete column from the data and meta data
tCorpus$delete_meta_columns | Delete column from the data and meta data
tCorpus$dfm | Create a document term matrix.
tCorpus$dtm | Create a document term matrix.
tCorpus$feats_to_columns | Cast the "feats" column in UDpipe tokens to columns
tCorpus$feature_associations | Get common nearby terms given a feature query
tCorpus$feature_stats | Feature statistics
tCorpus$feature_subset | Filter features
tCorpus$get | Access the data from a tCorpus
tCorpus$get_meta | Access the data from a tCorpus
tCorpus$kwic | Get keyword-in-context (KWIC) strings
tCorpus$lda_fit | Estimate a LDA topic model
tCorpus$preprocess | Preprocess feature
tCorpus$replace_dictionary | Replace tokens with dictionary match
tCorpus$search_contexts | Search for documents or sentences using Boolean queries
tCorpus$search_features | Find tokens using a Lucene-like search query
tCorpus$search_recode | Recode features in a tCorpus based on a search string
tCorpus$semnet | Create a semantic network based on the co-occurence of tokens in documents
tCorpus$semnet_window | Create a semantic network based on the co-occurence of tokens in token windows
tCorpus$set | Modify the token and meta data.tables of a tCorpus
tCorpus$set_levels | Change levels of factor columns
tCorpus$set_meta | Modify the token and meta data.tables of a tCorpus
tCorpus$set_meta_levels | Change levels of factor columns
tCorpus$set_meta_name | Change column names of data and meta data
tCorpus$set_name | Change column names of data and meta data
tCorpus$set_special | Designate column as columns with special meaning (token, lemma, POS, relation, parent)
tCorpus$subset | Subset a tCorpus
tCorpus$subset_meta | Subset a tCorpus
tCorpus$subset_query | Subset tCorpus token data using a query
tCorpus$top_features | Show top features
tCorpus_compare | Corpus comparison
tCorpus_create | Creating a tCorpus
tCorpus_data | Methods and functions for viewing, modifying and subsetting tCorpus data
tCorpus_docsim | Document similarity
tCorpus_features | Preprocessing, subsetting and analyzing features
tCorpus_modify_by_reference | Modify tCorpus by reference
tCorpus_querying | Use Boolean queries to analyze the tCorpus
tCorpus_semnet | Feature co-occurrence based semantic network analysis
tCorpus_topmod | Topic modeling
tokens_to_tcorpus | Create a tcorpus based on tokens (i.e. preprocessed texts)
tokenWindowOccurence | Gives the window in which a term occured in a matrix.
top_features | Show top features