Descriptive statistics about the text’s dimensions by genre, speaker, and act.
Everything we’ve done to the text so far, including the hand coding, is called text mining. By conducting some counts and visualizations here of the distributions in our variables of interest, we are moving into what data scientists call descriptive statistics. (And the next level of statistical complexity would be called predictive statistics, or modeling, or machine learning, or AI.)
Many digital text analysis projects are best served by careful descriptive statistics, and this is one of them.
Received from Doug Bruster via email.
First, let’s see which character has how many words.
Below is the same chart but showing only characters who use both prose and verse.
Let us focus on just the characters who use both genres. They are:
[1] "BAPTISTA" "BIANCA" "BIONDELLO" "GREMIO" "GRUMIO"
[6] "HORTENSIO" "KATHARINA" "LORD" "LUCENTIO" "PEDANT"
[11] "PETRUCHIO" "SLY" "TAILOR" "TRANIO" "VINCENTIO"
Let’s see how they mix across the five acts.
For attribution, please cite this work as
Hinrichs (2020, Oct. 17). Genre and Character in The Taming of the Shrew: 2 - Some Numbers. Retrieved from https://titus-and-shrew.netlify.app
BibTeX citation
@misc{hinrichs2020shrew-2, author = {Hinrichs, Lars}, title = {Genre and Character in The Taming of the Shrew: 2 - Some Numbers}, url = {https://titus-and-shrew.netlify.app}, year = {2020} }