| Abstract: |
With a focus on the English translation of the novel Tomb of Sand by Geetanjali Shree (translated by Daisy Rockwell), this study applies network analysis to explore character relationships, thematic connections, and narrative structures. Using Gephi and Python, the research maps characters, themes, and settings as nodes connected by relational edges derived from manual textual extraction. Network metrics such as degree, betweenness, and clustering coefficient quantify the prominence of narrative elements and their interconnections. The analysis identifies key figures that anchor the story's social and thematic architecture and uncovers clusters that align with central motifs of identity, displacement, and generational conflict. Specifically, Mother (Ma) emerges as the most central node with the highest betweenness centrality (191.0 in Gephi; 0.498 in Python), while the thematic network (166 nodes, 348 edges) and modularity scores (Q ≈ 0.42) establish stable community structures and highlight spatial nodes such as Borders and Wagah Border as key connectors within the narrative. By integrating computational modelling with close reading, the study introduces a transparent, replicable framework for literary network analysis and broadens the scope of digital humanities research on translated South Asian fiction. [ABSTRACT FROM AUTHOR] |