Digital Humanities and Society Studies

Articles

Decoding Gendered Symbolism and Motifs in Penina Muhando’s Nguzo Mama: A Computational Literary Analysis

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https://doi.org/10.54963/dhss.v1i1.2323
Volume 1 Issue 1 (2025)

Authors

  • Godfrey Wandwi

    Department of Digital Technologies and Information Sciences, Dar es Salaam Tumaini University, Dar es Salaam P.O. Box 77588, Tanzania
  • Felistas Mahonge

    Department of Digital Technologies and Information Sciences, Dar es Salaam Tumaini University, Dar es Salaam P.O. Box 77588, Tanzania

Received: 6 September 2025; Revised: 1 October 2025; Accepted: 13 November 2025; Published: 15 December 2025

This study offers a computational examination of gendered symbolism and recurring motifs in Penina Muhando’s Nguzo Mama, demonstrating how digital methods can deepen traditional literary interpretation. Employing natural language processing (NLP), topic modeling, and sentiment analysis, the research analyzes patterns of gendered language, thematic structures, and character interactions to uncover how femininity, motherhood, authority, and social agency are symbolically constructed within the narrative. The analysis identifies consistent lexical clusters and thematic networks that foreground women’s roles and highlight tensions embedded in socio-cultural expectations. Sentiment mapping and motif frequency analysis reveal how symbolic imagery and narrative positioning contribute to the negotiation of gender identities and power relations. These findings show that computational techniques can detect latent structures and recurring narrative patterns that may not be immediately apparent through close reading alone. Rather than replacing qualitative interpretation, the study positions computational analysis as a complementary and scalable framework that enhances interpretive depth. By integrating feminist literary theory with digital humanities methodologies, the research contributes to interdisciplinary scholarship and proposes a replicable model for analysing gender representation in literary texts. The study also reflects on methodological considerations, including algorithmic bias, contextual sensitivity, and the interpretive limits of quantitative analysis, underscoring the importance of balanced, theoretically informed application of digital tools in literary studies.

Keywords:

Computational Literary Analysis Gendered Motifs Symbolism Digital Humanities NLP Topic Modeling Sentiment Analysis Feminist Literary Studies

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