# Generate pairwise correlations for a vector of terms of interest.

Source:`R/calculate_corr.R`

`calculate_corr.Rd`

Generate pairwise correlations for a vector of terms of interest.

## Usage

```
calculate_corr(
df,
text_var,
terms,
min_freq = 10,
corr_limits = c(-1, 1),
n_corr = 75,
hashtags = FALSE,
mentions = FALSE,
clean_text = FALSE
)
```

## Arguments

- df
A dataframe where each row is a separate post.

- text_var
The variable containing the text which you want to explore.

- terms
The terms of interest. You can use multi-word phrases.

- min_freq
The minimum number of times a term must be observed to be considered.

- corr_limits
Numerical lower and upper bounds for correlations.

- n_corr
The number of correlations to include (begins with the most positive within the range specified in corr_limits).

- hashtags
Should hashtags be included?

- mentions
Should mentions be included?

- clean_text
Should the text variable be cleaned?

## Value

A list containing a summary table and a tidygraph object suitable for a network visualisation.

## Examples

```
{spinklr_export <- ParseR::sprinklr_export
x <- calculate_corr(
df = sprinklr_export,
text_var = Message,
terms = c("bobby", "trump"),
min_freq = 10,
corr_limits = c(-1, 1),
n_corr = 75,
hashtags = TRUE,
mentions = FALSE
)
viz_corr(x$viz)
}
```