THE LANGUAGE OF PERFORMANCE ON THE INDIAN STAGE: A PYTHON-ASSISTED CORPUS STUDY OF MAHESH DATTANI'S PLAYS
DOI:
https://doi.org/10.29121/shodhkosh.v7.i5s.2026.7212Keywords:
Indian English Drama, Corpus-Assisted Analysis, Computational Stylistics, Postcolonial Theatre, Python Text MiningAbstract [English]
This study blends close reading with corpus-assisted methods to examine how English mediates culture, gender, and identity in Mahesh Dattani’s drama. Using a curated, labelled corpus drawn from six plays like Dance Like a Man, Tara, Bravely Fought the Queen, On a Muggy Night in Mumbai, Seven Steps Around the Fire, and Thirty Days in September, the study attempts to analyse 38 dialogue excerpts (922 words; 362-type vocabulary). A Python workflow (pandas/regex) supports tokenization, frequency profiling, collocation checks, and concordance sampling by play, enabling comparative views of character voice, kinship terms, and conflict markers. Preliminary patterns indicate how English, as a postcolonial medium, frames intergenerational tensions and gendered power (e.g., character-centred lexis and familial address terms), while preserving localized cultural reference points. The results demonstrate the value of computational stylistics for Indian English theatre: lightweight, transparent metrics complement interpretive reading to surface recurring motifs across plays and to differentiate linguistic textures between domestic realism and identity-centric narratives. The paper contributes a replicable Python pipeline and a pilot corpus for Indian English drama studies, arguing that corpus-assisted analysis can sharpen debates on hybridity, performance, and the politics of language in contemporary Indian theatre.
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