Transforming Literature into Data

By Jade Harrison

When a short story becomes a dataset, the scale of interpretation transforms from individual moments to structural patterns.

As Lyric Hoover, a member of our Data Rangers explained, “When annotating ‘Patient Zero’ by Tananarive Due, I noticed how transforming literature into data allowed me to readily notice patterns in character dialogue, like Due’s tendency in this story to summarize conversations rather than write them out as regular dialogue.” Her reflection mirrors what I observe across the project. Once dialogue is tracked consistently, a writer’s structural tendencies become more visible to the reader.

When dialogue, character presence, and setting are quantified, patterns of emphasis become easier to track. We can see who speaks most often, which spaces recur, and how frequently certain interactions shape the narrative. This broader visibility allows us to interpret narrative structure at scale while remaining attentive to literary nuance.

Working between story and spreadsheet has clarified for me that data modeling and literary analysis function best when they shape one another.

Related:

• The Black Short Story Project