Reframing Narrative Analysis: Computational Approaches to Abdulrazak Gurnah’s by the Sea

This study investigates the integration of computational approaches into literary analysis, with a specific focus on Abdulrazak Gurnah’s By the Sea (2001), situating the novel within a comparative computational corpus of approximately 200 literary texts used to establish broader thematic and sentiment baselines. exploring how digital tools can illuminate narrative structures, themes, and character dynamics. By employing natural language processing (NLP), topic modeling, sentiment analysis, and social network analysis, the researchers examine the novel’s exploration of identity and displacement, memory and truth, cultural conflicts, and the postcolonial experience, revealing patterns and thematic structures that complement traditional close reading. Computational analysis highlights recurring motifs of solitude, conflict, and social justice, as well as the nuanced interplay between character relationships and narrative voice, offering a systematic perspective on Gurnah’s complex narrative architecture. The study demonstrates that computational methods enrich literary scholarship by providing empirical insights into themes, emotional trajectories, and social networks, while still honouring the interpretive depth of humanistic inquiry. By integrating computational techniques with traditional literary interpretation, the study reveals that digital humanities approaches can enrich understanding of narrative complexity. The research also discusses methodological limitations, including interpretive challenges in large-scale textual analysis, and proposes future applications of machine learning for exploring nuanced narrative features in postcolonial literature.

computational approaches, digital humanity, natural language processing, topic modeling, sentiment analysis, narrative structure, literary analysis, postcolonial literature,

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