corpus_analytics()This is a helpful addition to ConversationAlign that
will generate a variety of corpus analytics (e.g., word count,
type-token-ratio) for your conversation corpus. The output is in a
summary table that is readily exportable to to the specific journal
format of your choice using any number of packages such as
flextable or tinytable.
Generate your corpus analytics on the dataframe you created with
prep_dyads.
Arguments to
corpus_analytics include:
1)
dat_prep= dataframe created by
prep_dyads()function
NurseryRhymes_Analytics <- corpus_analytics(dat_prep=NurseryRhymes_Prepped)
knitr::kable(head(NurseryRhymes_Analytics, 15), format = "simple", digits = 2)| measure | mean | stdev | min | max |
|---|---|---|---|---|
| total number of conversations | 3.00 | NA | NA | NA |
| token count all conversations (raw) | 1506.00 | NA | NA | NA |
| token count all conversations (post-cleaning) | 1032.00 | NA | NA | NA |
| exchange count (by conversation) | 38.00 | 13.11 | 24.00 | 50.00 |
| word count raw (by conversation) | 502.00 | 47.03 | 456.00 | 550.00 |
| word count clean (by conversation) | 344.00 | 48.66 | 312.00 | 400.00 |
| cleaning retention rate (by conversation) | 0.68 | 0.04 | 0.64 | 0.73 |
| morphemes-per-word (by conversation) | 1.00 | 0.00 | 1.00 | 1.00 |
| letters-per-word (by conversation) | 4.22 | 0.14 | 4.12 | 4.38 |
| lexical frequency lg10 (by conversation) | 3.67 | 0.18 | 3.48 | 3.84 |
| words-per-turn raw (by conversation) | 7.08 | 2.13 | 5.50 | 9.50 |
| words-per-turn clean (by conversation) | 4.83 | 1.44 | 4.00 | 6.50 |
| TTR raw (by conversation) | 0.03 | 0.01 | 0.02 | 0.04 |
| TTR clean (by conversation) | 0.04 | 0.02 | 0.02 | 0.05 |
`