`R/3_1_textSimilarity.R`

`textSimilarity.Rd`

Compute the semantic similarity between two text variables.

`textSimilarity(x, y, method = "cosine", center = TRUE, scale = FALSE)`

- x
Word embeddings from textEmbed.

- y
Word embeddings from textEmbed.

- method
(character) Character string describing type of measure to be computed. Default is "cosine" (see also "spearmen", "pearson" as well as measures from textDistance() (which here is computed as 1 - textDistance) including "euclidean", "maximum", "manhattan", "canberra", "binary" and "minkowski").

- center
(boolean; from base::scale) If center is TRUE then centering is done by subtracting the column means (omitting NAs) of x from their corresponding columns, and if center is FALSE, no centering is done.

- scale
(boolean; from base::scale) If scale is TRUE then scaling is done by dividing the (centered) columns of x by their standard deviations if center is TRUE, and the root mean square otherwise.

A vector comprising semantic similarity scores. The closer the value is to 1 when using the default method, "cosine", the higher the semantic similarity.

See `textDistance`

and `textSimilarityNorm`

.

```
#Compute the semantic similarity between the embeddings from "harmonytext" and "satisfactiontext".
if (FALSE) {
similarity_scores <- textSimilarity(
x = word_embeddings_4$texts$harmonytext,
y = word_embeddings_4$texts$satisfactiontext
)
#Show information about how similarity_scores were constructed.
comment(similarity_scores)
}
```