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Get Text Embeddings by Averaging Word Embeddings

textstat_embedding.Rd

textstat_embedding() takes a 'quanteda' dfm. embed_docs() is a more versatile function for which acts directly on either a character vector or a column of texts in a dataframe.

Usage

textstat_embedding(
  dfm,
  model,
  w = NULL,
  method = "mean",
  output_embeddings = FALSE
)

embed_docs(x, ...)

# Default S3 method
embed_docs(
  x,
  model,
  w = NULL,
  method = "mean",
  ...,
  tolower = TRUE,
  output_embeddings = FALSE
)

# S3 method for class 'data.frame'
embed_docs(
  x,
  text_col,
  model,
  id_col = NULL,
  w = NULL,
  method = "mean",
  ...,
  .keep_all = FALSE,
  tolower = TRUE,
  output_embeddings = FALSE
)

Arguments

dfm

a quanteda dfm

model

an embeddings object. For embed_docs(), model can alternatively be a function that takes a character vector and outputs a dataframe with a row for each element of the input.

w

optional weighting for embeddings in model if model is an embeddings object. See average_embedding().

method

method to use for averaging. See average_embedding(). Note that method = "median" does not use matrix operations and may therefore be slow for datasets with many documents.

output_embeddings

FALSE (the default) returns a tibble. TRUE returns an embeddings object. See 'Value' for details.

x

a character vector, a data frame, or data frame extension (e.g. a tibble)

...

additional parameters to pass to quanteda::tokens() or to the user-specified modeling function

tolower

logical. Convert all text to lowercase? If model is an embeddings object, this value is passed to quanteda::dfm().

text_col

string. a column of texts for which to compute embeddings

id_col

optional string. column of unique document ids

.keep_all

logical. Keep all columns from input? Ignored if output_embeddings = TRUE.

Value

If output_embeddings = FALSE, a tibble with columns doc_id, and dim_1, dim_2, etc. or similar. If .keep_all = TRUE, the new columns will appear after existing ones. If output_embeddings = TRUE, an embeddings object with document ids as rownames.

See also

embed_tokens()

Examples

texts <- c("this says one thing", "and this says another")
texts_embeddings <- embed_docs(texts, glove_twitter_25d)
texts_embeddings
#> # A tibble: 2 × 26
#>   doc_id  dim_1 dim_2  dim_3  dim_4   dim_5  dim_6 dim_7  dim_8   dim_9  dim_10
#>   <chr>   <dbl> <dbl>  <dbl>  <dbl>   <dbl>  <dbl> <dbl>  <dbl>   <dbl>   <dbl>
#> 1 text1   0.114 0.167 0.180  -0.144 -0.0492 -0.465  1.77 -0.161 -0.414  -0.0989
#> 2 text2  -0.289 0.297 0.0145 -0.108 -0.248  -0.495  1.58 -0.234 -0.0946 -0.177 
#> # ℹ 15 more variables: dim_11 <dbl>, dim_12 <dbl>, dim_13 <dbl>, dim_14 <dbl>,
#> #   dim_15 <dbl>, dim_16 <dbl>, dim_17 <dbl>, dim_18 <dbl>, dim_19 <dbl>,
#> #   dim_20 <dbl>, dim_21 <dbl>, dim_22 <dbl>, dim_23 <dbl>, dim_24 <dbl>,
#> #   dim_25 <dbl>

# quanteda workflow
library(quanteda)
texts_dfm <- dfm(tokens(texts))

texts_embeddings <- textstat_embedding(texts_dfm, glove_twitter_25d)
texts_embeddings
#> # A tibble: 2 × 26
#>   doc_id  dim_1 dim_2  dim_3  dim_4   dim_5  dim_6 dim_7  dim_8   dim_9  dim_10
#>   <chr>   <dbl> <dbl>  <dbl>  <dbl>   <dbl>  <dbl> <dbl>  <dbl>   <dbl>   <dbl>
#> 1 text1   0.114 0.167 0.180  -0.144 -0.0492 -0.465  1.77 -0.161 -0.414  -0.0989
#> 2 text2  -0.289 0.297 0.0145 -0.108 -0.248  -0.495  1.58 -0.234 -0.0946 -0.177 
#> # ℹ 15 more variables: dim_11 <dbl>, dim_12 <dbl>, dim_13 <dbl>, dim_14 <dbl>,
#> #   dim_15 <dbl>, dim_16 <dbl>, dim_17 <dbl>, dim_18 <dbl>, dim_19 <dbl>,
#> #   dim_20 <dbl>, dim_21 <dbl>, dim_22 <dbl>, dim_23 <dbl>, dim_24 <dbl>,
#> #   dim_25 <dbl>

# dplyr workflow
texts_df <- data.frame(text = texts)
texts_embeddings <- texts_df |> embed_docs("text", glove_twitter_25d)
texts_embeddings
#> # A tibble: 2 × 26
#>   doc_id  dim_1 dim_2  dim_3  dim_4   dim_5  dim_6 dim_7  dim_8   dim_9  dim_10
#>   <chr>   <dbl> <dbl>  <dbl>  <dbl>   <dbl>  <dbl> <dbl>  <dbl>   <dbl>   <dbl>
#> 1 text1   0.114 0.167 0.180  -0.144 -0.0492 -0.465  1.77 -0.161 -0.414  -0.0989
#> 2 text2  -0.289 0.297 0.0145 -0.108 -0.248  -0.495  1.58 -0.234 -0.0946 -0.177 
#> # ℹ 15 more variables: dim_11 <dbl>, dim_12 <dbl>, dim_13 <dbl>, dim_14 <dbl>,
#> #   dim_15 <dbl>, dim_16 <dbl>, dim_17 <dbl>, dim_18 <dbl>, dim_19 <dbl>,
#> #   dim_20 <dbl>, dim_21 <dbl>, dim_22 <dbl>, dim_23 <dbl>, dim_24 <dbl>,
#> #   dim_25 <dbl>