In mkearney/dict: Word-Based Dictionaries for Natural Language

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dict

The goal of dict is to make it easy to create, modify, and use word-based dictionaries for analyzing natural language texts. In other words, this package is designed to create sentiment-analysis like tools for measuring the extent to which natural language reflects (positively and/or negatively) any user-defined dimension or topic (e.g., politics, sports, emotions, active, pass, medical, philosophical, etc.).

Installation

You can install the released version of dict from CRAN with:

install.packages("dict")

You can install the developmernt version of dict from Github with:

remotes::install_github("mkearney/dict")

Example

Create vectors of positively and negatively identifying words for a simple "valence" dimension.

## load package
library(dict)

## vector of positive words
pos <- c("like", "love", "amazing", "excellent", "great", "fantastic",
  "incredible", "awesome", "best", "favorite", "fan", "fun", "enjoyed",
  "good", "solid", "better", "soooo", "happy")

## vetor of negative words
neg <- c("hate", "loathe", "dislike", "awful", "horrible", "worst",
  "miserable", "ruin", "ruining", "destroy", "destroyed", "destroying",
  "pathetic", "hated", "unhappy", "terrible")

Create dictionaries

Create a dictionary using only positively-coded words or both positively and negatively coded words.

## create dictionary using only positive words
only_pos <- dict(pos)

## create dictionary using both positive and negative words
d <- dict(list(pos = pos, neg = neg))

## view up to n entries of dictionary
print(d, n = 15)

Use word dictionary

Apply a dictionary to some example text:

## example text
txt <- c("love amazing excellent good",
  "hate loathe horrifies unhappy terrible",
  "awesome best hateful hated worst")

## get estimates for each element of txt using pos/neg dictionary
d$score(txt)

## store only the overall score in a tibble
tibble::tibble(
  text  = txt,
  score = d$score_score(txt)
)

Export dictionary via R package

Export word dictionaries as super fast packages using this wrapper around usethis::create_package()

## create package path via temp directory
path_pkg <- file.path(tempdir(), "simpleexample")

## create R package featuring d
create_dict_pkg(d, path_pkg)

## test new package's score function on txt vector
simpleexample::score(txt)

Compare the speed of the default returned function (written in R) versus the optimized version in the standalone package (written in C)

## analyzeSentiment() won't work unless you load the whole library
library(SentimentAnalysis)

## compare speed
bm <- bench::mark(
  SentimentAnalysis = analyzeSentiment(txt),
  syuzhet = syuzhet::get_sentiment(txt),
  dict_fun = d$score(txt),
  dict_pkg = simpleexample::score(txt),
  relative = TRUE,
  check = FALSE,
  iterations = 30
)

## view results
bm

## view plot
ggplot2::autoplot(bm)