Function reference • keywordr

Setup and classification

kwresearch(): Creates an object of the kwresearch class

kwr_import(): Imports queries to a kwresearch object

kwr_import_mm(): Imports Marketing Miner CSV file(s) to an empty kwresearch object

kwr_prune(): Removes unwanted queries according to YAML recipes

kwr_prune_long_queries(): From pruned data removes queries longer than a specific number of characters

kwr_classify(): Classifies queries based on recipes in a YAML file

Research

kwr_collocations(): Finds collocations, i.e. multiword phrases that are more likely than their single words

kwr_long_queries(): Outputs queries longer than a specific number of characters

kwr_ngrams(): Generates n-grams from queries

kwr_subqueries(): Generates n-grams from queries and filter only those that match any existing query

Output results

kwr_classified_queries(): Outputs classified queries

kwr_clean_queries(): Outputs cleaned (normalized and accentized) queries

kwr_dimension_names(): Gets the names of all dimensions

kwr_dimension_table(): Outputs frequency table of a given dimension

kwr_pruned_queries(): Outputs pruned queries

kwr_queries(): Outputs the most processed queries

kwr_removed_queries(): Outputs queries removed by kwr_prune

kwr_source_queries(): Outputs raw, source queries

kwr_summary(): Prints number of queries in all phases of processing

kwr_unclassified_queries(): List queries that are not classified in all or specified dimensions

Helpers and utilities

kwr_add_pattern(): Adds a new regex pattern to a pruning or classification recipe

kwr_build_regex(): Creates regular expression from a single string

kwr_dimension_names(): Gets the names of all dimensions

kwr_remove_stopwords(): Removes stopwords from a dataset, e.g. n-grams

kwr_stopwords(): Return stopwords as a character vector

kwr_test_regex(): Explore a regex pattern applied on queries

kwr_use_stopwords(): Set a stopword list to use with n-gram functions