Tracing Intersectionality, Individual and Familial Struggle in Morrison’s Novels: A Digital Humanities Study

Abstract

Since close reading is a time-consuming activity to explore quantified information from literary
works, the digital natives of the modern age have started to build big databases of literary works
to knowledge patterns. This study aims to use the text mining technique to extract key themes
and characters as a previewing and digitized summarization technique. The research data
comprises Nobel laureate Toni Morrison’s four novels: Beloved, A Mercy, The Bluest Eye and
Sula. The study in hand employs a mixed-methods technique because the data have qualitative,
statistical and visual characteristics. The generated data have been discussed with Sinclair and
Rockwell’s Hermeneutica theory. Cirrus tool presents an interactive word cloud that comprises
textual, visual and statistical data to preview key motifs and characters. Major findings reveal
that the word clouds of four novels verify the recurring themes and characters from the selected
texts. The key themes of the selected novels are slavery, family, home, human bondage, race,
and racism, and they can be instantly extracted from big data with the help of the Cirrus tool.
This study has implications for students of literature to visualize themes and characters as
previewing, memorization and pedagogical strategies.