Title: Dictionaries for the 'SemNetCleaner' Package
Version: 0.2.1
Date: 2025-05-08
Maintainer: Alexander P. Christensen <alexpaulchristensen@gmail.com>
Description: Implements dictionaries that can be used in the 'SemNetCleaner' package. Also includes several functions aimed at facilitating the text cleaning analysis in the 'SemNetCleaner' package. This package is designed to integrate and update word lists and dictionaries based on each user's individual needs by allowing users to store and save their own dictionaries. Dictionaries can be added to the 'SemNetDictionaries' package by submitting user-defined dictionaries to https://github.com/AlexChristensen/SemNetDictionaries.
Depends: R (≥ 3.6.0)
License: GPL (≥ 3.0)
Suggests: easycsv, ggplot2, gridExtra, htmlTable, knitr, markdown, patchwork, rmarkdown, shiny, shinyalert, shinyjs
URL: https://github.com/AlexChristensen/SemNetDictionaries
BugReports: https://github.com/AlexChristensen/SemNetDictionaries/issues
NeedsCompilation: no
Encoding: UTF-8
LazyData: true
VignetteBuilder: knitr
RoxygenNote: 7.3.2
Packaged: 2025-05-08 14:23:43 UTC; alextops
Author: Alexander P. Christensen ORCID iD [aut, cre]
Repository: CRAN
Date/Publication: 2025-05-08 15:00:02 UTC

SemNetDictionaries–package

Description

Implements dictionaries that can be used in the SemNetCleaner-package. Also includes several functions aimed at facilitating the text cleaning analysis in the SemNetCleaner-package. This package is designed to integrate and update word lists and dictionaries based on each user's individual needs by allowing users to store and save their own dictionaries. Dictionaries can be added to the SemNetDictionaries package by submitting user-defined dictionaries to https://github.com/AlexChristensen/SemNetDictionaries.

Author(s)

Alexander Christensen <alexpaulchristensen@gmail.com>

See Also

Useful links:

Shiny App to Play WoRdle

Description

An interactive Shiny application for playing WoRdle

Usage

ShinyWoRdle()

Examples


if(interactive())
{ShinyWoRdle()}

Animals Dictionary

Description

A database of possible animals responses (n = 1211)

Usage

data(animals.dictionary)

Format

animals.dictionary (vector, length = 1211)

Details

To add additional animals to the dictionary, please make an appendix dictionary (append.dictionary)

Examples

data("animals.dictionary")

Animals Moniker

Description

A database of possible animals monikers and common spelling errors

Usage

data(animals.moniker)

Format

animals.moniker (list, length = 236)

Details

To add additional animals monikers to the database, please submit a pull request or issue to https://github.com/AlexChristensen/SemNetDictionaries

Examples

data("animals.moniker")

Appendix Dictionary

Description

A function designed to create post-hoc dictionaries in the SemNetDictionaries package. This allows for new semantic categories or word lists to be saved for future use (i.e., your own personal dictionary). Dictionaries created using this function can either be saved as an R object to your global environment or as a .rds file on your current computer. Open-source community-derived dictionaries can be uploaded to and downloaded from https://github.com/AlexChristensen/SemNetDictionaries

Usage

append.dictionary(
  ...,
  dictionary.name = "appendix",
  save.location = c("envir", "wd", "choose", "path"),
  path = NULL,
  textcleaner = FALSE,
  package = FALSE
)

Arguments

...

Character vector. A vector of words to create or add to a dictionary

dictionary.name

Character. Name of dictionary to create or add words to. Defaults to "appendix". Input a name to create or add to an existing dictionary. This function with automatically name files with the "*.dictionary.rds" suffix

save.location

Character. A choice for where to store appendix dictionary. Defaults to "envir".

  • "envir": Returns dictionary as a vector object to R's global environment

  • "wd": Saves dictionary to working directory. Useful for storing dictionaries alongside projects

  • "choose": User chooses a directory for more permanent storage. This will allow you to use this dictionary in the future

  • "path": User specifies a path to a directory if it is already known. This will allow direct updates to the directory and bypass the prompts in the save/update menus. This will also allow you to use this dictionary in the future

path

Character. A path to an existing directory. Only necessary for save.location = "path"

textcleaner

Boolean. Argument for skipping asking to save the dictionary twice. Defaults to FALSE. If TRUE, then asking to save the dictionary will be skipped.

package

Boolean. Argument not meant for user use. Allows me to update the package's dictionaries efficiently

Details

Appendix dictionaries are useful for storing spelling definitions that are not available in the SemNetDictionaries package. This function enables the storage of personalized dictionaries, which can be used in combination with other dictionaries to facilitate the cleaning of text data.

Dictionaries are either stored in R's global environment, where they will be deleted once R is closed (unless you save them), or in a directory you choose. A menu will pop-up asking whether you would like to save or update your dictionary. You have two options:

To save your dictionary file, you can either:

Note that save.location = "choose" and save.location = "path" will automatically update your dictionary if there is a file with the same name enter into the dictionary.name argument.

To find where your dictionaries are stored, use the find.dictionaries function. These dictionaries are only stored on your private computer and must either be publicly shared or transferred to other computers in order to use them elsewhere. If you would like to share a dictionary for others to use, then please submit a pull request or post an issue with your dictionary on my GitHub: AlexChristensen/SemNetDictionaries.

Author(s)

Alexander Christensen <alexpaulchristensen@gmail.com>

See Also

find.dictionaries to find where dictionaries are stored, dictionaries to identify dictionaries in SemNetDictionaries

Examples

# Create a dictionary
new.dictionary <- append.dictionary(c("words","are","fun"), save.location = "envir")

British-US English Conversions

Description

A database to convert between British and US spellings (n = 780)

Usage

data(brit2us)

Format

brit2us (list, length = 780)

Examples

data("brit2us")

Corpus of Contemporary American English Dictionary

Description

A general dictionary of over 80,000 words from the Corpus of Contemporary American English derived from https://www.wordfrequency.info/samples.asp.

Usage

data(coca.dictionary)

Format

coca.dictionary (vector, length = 80381)

Details

To add additional words to the dictionary, please make an appendix dictionary (append.dictionary)

Examples

data("coca.dictionary")

Corpus of Contemporary American English Moniker

Description

A database of word forms for the Corpus of Contemporary American English dictionary

Usage

data(coca.moniker)

Format

coca.moniker (list, length = 20267)

Details

To add additional COCA monikers to the database, please submit a pull request or issue to https://github.com/AlexChristensen/SemNetDictionaries

Examples

data("coca.moniker")

Corpus of Contemporary American English and Hunspell Combined Dictionary

Description

A general dictionary of over 109,000 words from the Corpus of Contemporary American English dictionary (coca.dictionary) and Hunspell dictionary (hunspell.dictionary).

Usage

data(cocaspell.dictionary)

Format

cocaspell.dictionary (vector, length = 109169)

Details

To add additional words to the dictionary, please make an appendix dictionary (append.dictionary)

Examples

data("cocaspell.dictionary")

Corpus of Contemporary American English and Hunspell Moniker

Description

A database of word forms for the Corpus of Contemporary American English and Hunspell dictionaries

Usage

data(cocaspell.moniker)

Format

cocaspell.moniker (list, length = 29610)

Details

To add additional COCA and Hunspell monikers to the database, please submit a pull request or issue to https://github.com/AlexChristensen/SemNetDictionaries

Examples

data("cocaspell.moniker")

List Names of Dictionaries in 'SemNetDictionaries'

Description

A wrapper function to identify all dictionaries included in SemNetDictionaries

Usage

dictionaries(quiet)

Arguments

quiet

Boolean. Determines whether the return should be quiet (does not print dictionaries). Defaults to FALSE

Value

Returns the names of dictionaries in SemNetDictionaries

Author(s)

Alexander Christensen <alexpaulchristensen@gmail.com>

See Also

find.dictionaries to find where dictionaries are stored, append.dictionary to create a new dictionary

Examples

# List names of dictionaries in 'SemNetDictionaries'
dictionaries()

Finds Names and Locations of Appendix Dictionaries

Description

A wrapper function to identify the save location of appendix dictionaries from append.dictionary

Usage

find.dictionaries(..., add.path = NULL)

Arguments

...

Vector. Appendix dictionary files names (if they are known). If left empty, the function will search across all files for files in folders on your desktop that end in *.dictionary.rds. This search takes a few seconds to complete (see examples for your computer's exact timing)

add.path

Character. Path to additional dictionaries to be found. DOES NOT search recursively (through all folders in path) to avoid time intensive search. Set to "choose" to open an interactive directory explorer

Value

names

Returns the names of the appendix dictionary file(s) found on your computer

files

Returns the dictionary file(s) that are stored in each given path. If there is no output (e.g., character(0)), then no appendix dictionary file exists (one can be created using the append.dictionary function)

Author(s)

Alexander Christensen <alexpaulchristensen@gmail.com>

See Also

append.dictionary to create a new dictionary, dictionaries to identify dictionaries in SemNetDictionaries, and load.dictionaries to load multiple dictionaries

Examples

# Make a dictionary
example.dictionary <- append.dictionary(c("words","are","fun"), save.location = "envir")
 
# Dictionary can now be found
find.dictionaries("example")

# No appendix dictionaries found
find.dictionaries()

# For your computer's timing to complete search
t0 <- Sys.time()
find.dictionaries()
Sys.time() - t0

Fruits Dictionary

Description

A database of possible fruits responses (n = 488)

Usage

data(fruits.dictionary)

Format

fruits.dictionary (vector, length = 488)

Details

To add additional fruits to the dictionary, please make an appendix dictionary (append.dictionary)

Examples

data("fruits.dictionary")

Fruits Moniker

Description

A database of possible fruits monikers and common spelling errors

Usage

data(fruits.moniker)

Format

fruits.moniker (list, length = 39)

Details

To add additional fruits monikers to the database, please submit a pull request or issue to https://github.com/AlexChristensen/SemNetDictionaries

Examples

data("fruits.moniker")

General Dictionary

Description

A general dictionary of over 370,000 words (n = 370,103) derived from https://github.com/dwyl/english-words. All punctuation have been removed.

Usage

data(general.dictionary)

Format

general.dictionary (vector, length = 370103)

Details

To add additional words to the dictionary, please make an appendix dictionary (append.dictionary)

Examples

data("general.dictionary")

'Good' Synonyms Dictionary

Description

A database of possible good synonym responses (n = 284) To add additional good synonyms to the dictionary, please make an appendix dictionary (append.dictionary)

Usage

data(good.dictionary)

Format

good.dictionary (vector, length = 284)

Examples

data("good.dictionary")

'Good' Moniker

Description

A database of possible good monikers and common spelling errors

Usage

data(good.moniker)

Format

good.moniker (list, length = 4)

Details

To add additional good monikers to the database, please submit a pull request or issue to https://github.com/AlexChristensen/SemNetDictionaries

Examples

data("good.moniker")

'Hot' Synonyms Dictionary

Description

A database of possible hot synonym responses (n = 281) To add additional hot synonyms to the dictionary, please make an appendix dictionary (append.dictionary)

Usage

data(hot.dictionary)

Format

hot.dictionary (vector, length = 281)

Examples

data("hot.dictionary")

Hot Moniker

Description

A database of possible hot monikers and common spelling errors

Usage

data(hot.moniker)

Format

hot.moniker (list, length = 15)

Details

To add additional hot monikers to the database, please submit a pull request or issue to https://github.com/AlexChristensen/SemNetDictionaries

Examples

data("hot.moniker")

hunspell Dictionary

Description

A general dictionary of over 62,000 words from the hunspell dictionary derived from http://wordlist.aspell.net/dicts/.

Usage

data(hunspell.dictionary)

Format

hunspell.dictionary (vector, length = 62893)

Details

To add additional words to the dictionary, please make an appendix dictionary (append.dictionary)

Examples

data("hunspell.dictionary")

Jobs Dictionary

Description

A database of possible jobs and related words (n = 1471)

Usage

data(jobs.dictionary)

Format

jobs.dictionary (vector, length = 1471)

Details

To add additional jobs to the dictionary, please make an appendix dictionary (append.dictionary)

Examples

data("jobs.dictionary")

Jobs Moniker

Description

A database of possible jobs monikers and common spelling errors

Usage

data(jobs.moniker)

Format

jobs.moniker (list, length = 117)

Details

To add additional jobs monikers to the database, please submit a pull request or issue to https://github.com/AlexChristensen/SemNetDictionaries

Examples

data("jobs.moniker")

Load Dictionaries

Description

A wrapper function to load dictionaries into the 'SemNetCleaner' package. Searches for dictionaries in R's global environment, the SemNetDictionaries package, and on your computer. Outputs a unique word list that is combined from all dictionaries entered in the dictionary argument

Usage

load.dictionaries(..., add.path = NULL)

Arguments

...

Character. Dictionaries to load

Dictionaries in your global environment MUST be objects called "*.dictionary" (see examples)

add.path

Character. Path to additional dictionaries to be found. DOES NOT search recursively (through all folders in path) to avoid time intensive search. Set to "choose" to open an interactive directory explorer

dictionaries will identify dictionaries in the SemNetDictionaries package

find.dictionaries will identify dictionaries on your computer

Value

Returns a vector of unique words that have been combined and alphabetized from the specified dictionaries

Author(s)

Alexander Christensen <alexpaulchristensen@gmail.com>

Examples

# Find dictionaries to load
dictionaries()

# Load "animals" dictionary
load.dictionaries("animals")

# Create a dictionary
new.dictionary <- append.dictionary("words", "are", "fun")

# Load created dictionary
load.dictionaries("new")

# Load animals and new dictionary
load.dictionaries("animals", "new")

# Single letter dictionary
load.dictionaries("d")

# Multiple letters dictionary
load.dictionaries("a", "d")

# Category and letters dictionary
load.dictionaries("animals", "a")

Load Monikers

Description

A wrapper function to load monikers into the 'SemNetCleaner' package. Searches for monikers in R's SemNetDictionaries package. Outputs a unique word list that is combined from all dictionaries entered in the moniker argument

Usage

load.monikers(moniker, vector = TRUE)

Arguments

moniker

Character vector. monikers to load (must be a dictionary in dictionaries)

vector

Boolean. Should output be a vector? If FALSE, then output is a list. Defaults to TRUE

Value

Returns a vector of unique words that have been combined and alphabetized from the specified monikers

Author(s)

Alexander Christensen <alexpaulchristensen@gmail.com>

Examples

#find dictionaries to load
dictionaries()

#load "animals" monikers
load.monikers("animals")

Most Common Dictionary

Description

A general dictionary of 10,000 of the most common U.S. English words derived from https://github.com/first20hours/google-10000-english.

Usage

data(most_common.dictionary)

Format

most_common.dictionary (vector, length = 9329)

Details

To add additional words to the dictionary, please make an appendix dictionary (append.dictionary)

Examples

data("most_common.dictionary")

Stop Words Dictionary

Description

A selection of stop words that can be removed from semantic responses (n = 56)

Usage

data(stop_words.dictionary)

Format

stop_words.dictionary (vector, length = 56)

Details

To add additional animals to the dictionary, please make an appendix dictionary (append.dictionary)

Examples

data("stop_words.dictionary")

Vegetables Dictionary

Description

A database of possible vegetables responses (n = 284)

Usage

data(vegetables.dictionary)

Format

vegetables.dictionary (vector, length = 284)

Details

To add additional vegetables to the dictionary, please make an appendix dictionary (append.dictionary)

Examples

data("vegetables.dictionary")

Vegetables Moniker

Description

A database of possible vegetables monikers and common spelling errors

Usage

data(vegetables.moniker)

Format

vegetables.moniker (list, length = 35)

Details

To add additional vegetables monikers to the database, please submit a pull request or issue to https://github.com/AlexChristensen/SemNetDictionaries

Examples

data("vegetables.moniker")