In scottmanski/TAGAM:

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)

TAGAM

The goal of TAGAM is to streamline the use of word embeddings in text analysis. The package is designed to take raw textual descriptions and transform the information for use in your analysis. The package also includes functions for running the generalized additive model framework described in XXX.

Installation

You can install the development version from GitHub with:

# install.packages("devtools")
devtools::install_github("scottmanski/TAGAM")

Example

This is a basic example which shows you how to solve a common problem:

library(TAGAM)
temp <- tempfile()
download.file("http://nlp.stanford.edu/data/wordvecs/glove.6B.zip", temp)

embedding_matrix <- read.table(unz(temp, "glove.6B.300d.txt"), quote = "",
                               comment.char = "", stringsAsFactors = FALSE)
word_embeddings <- formatWordEmbeddings(embedding_matrix, normalize = TRUE)

library(TAGAM)
a <- "statistic"
b <- "statistics"
cs(a, b, word_embeddings_subset)

library(tidyverse)
library(tidytext)
D <- c("Statistics is great!",
       "My dog is fluffy",
       "What is your favorite class?")
x <- tibble(line = 1:length(D), text = D) %>%
  unnest_tokens(word, text)

w <- c("statistics", "dog", "fluffy", "favorite", "class")

cs.matrix(x, words = w, word_embeddings_subset)