Applies word embeddings from a given decontextualized static space (such as from Latent Semantic Analyses) to all character variables

textEmbedStatic(
df,
space,
tk_df = "null",
aggregation_from_tokens_to_texts = "mean",
dim_name = FALSE,
tolower = FALSE
)

## Arguments

df

dataframe that at least contains one character column.

space

decontextualized/static space with a column called "words" and the semantic representations are in columns called Dim1, Dim2 (or V1, V2, ...) and so on (from textSpace, which is not included in the current text package).

tk_df

default "null"; option to use either the "tk" of "df" space (if using textSpace, which has not been implemented yet).

aggregation_from_tokens_to_texts

method to aggregate semantic representation when their are more than a single word. (default is "mean"; see also "min" and "max", "concatenate" and "normalize")

dim_name

Boolean, if TRUE append the variable name after all variable-names in the output. (This differentiates between word embedding dimension names; e.g., Dim1_text_variable_name)

tolower

(boolean) Lower case input.

## Value

A list with tibbles for each character variable. Each tibble comprises a column with the text, followed by columns representing the semantic representations of the text. The tibbles are called the same as the original variable.

see textEmbed