# ConversationAlign_Step4_Analytics

### corpus_analytics()

#### Jamie Reilly, Ben Sacks, Ginny Ulichney, Gus Cooney, Chelsea Helion

#### July 30, 2025

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

`