Exploring Indian Loanwords in Netflix Subtitles: A Comparative Analysis of Google Translate and WhatsApp Meta Translator

This research paper explores the challenges of translating Indian loanwords in Netflix series such as Chamkila (2024), Sector 36 (2024), Maharaj (2024), Bhakshak (2024), and The Great Indian Kapil Show (2024). The objective is to conduct a comparative analysis of the translation approaches used by Google Translate and WhatsApp Meta AI, evaluating their efficiency in conveying cultural meaning and promoting cross-cultural understanding. The qualitative methodology applies the Loanwords Adaptation Theory to assess the translation outputs of both tools for a selected set of 30 loanwords. The Findings depict that Google Translate predominantly employs a retention strategy. However, WhatsApp Meta AI adopts an adaptation strategy, offering context-rich translations that enhance cross-cultural communication on Netflix. Furthermore, the study concludes that WhatsApp Meta AI serves more effective translation of Loanwords than Google Translate does. This research contributes to a broader understanding of the role AI-based translation tools play in navigating the challenges of translating culturally rich content. It also recommends that future translation technologies incorporate adaptive strategies to improve the accessibility of culturally significant terms, thereby enhancing cross-cultural communication in audiovisual media.

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Publication Details

Journal
Wah Academia Journal of Social Sciences
Published
2025-05-15
DOI
https://doi.org/10.63954/wajss.4.1.21.2025
Primary Topic
Subtitles and Audiovisual Media
Type
article
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article

Exploring Indian Loanwords in Netflix Subtitles: A Comparative Analysis of Google Translate and WhatsApp Meta Translator

Seemab Jamil Ghouri, Komal Zahid
Wah Academia Journal of Social Sciences
Subtitles and Audiovisual Media
article

Exploring Indian Loanwords in Netflix Subtitles: A Comparative Analysis of Google Translate and WhatsApp Meta Translator

Seemab Jamil Ghouri, Komal Zahid
article en

Abstract

This research paper explores the challenges of translating Indian loanwords in Netflix series such as Chamkila (2024), Sector 36 (2024), Maharaj (2024), Bhakshak (2024), and The Great Indian Kapil Show (2024). The objective is to conduct a comparative analysis of the translation approaches used by Google Translate and WhatsApp Meta AI, evaluating their efficiency in conveying cultural meaning and promoting cross-cultural understanding. The qualitative methodology applies the Loanwords Adaptation Theory to assess the translation outputs of both tools for a selected set of 30 loanwords. The Findings depict that Google Translate predominantly employs a retention strategy. However, WhatsApp Meta AI adopts an adaptation strategy, offering context-rich translations that enhance cross-cultural communication on Netflix. Furthermore, the study concludes that WhatsApp Meta AI serves more effective translation of Loanwords than Google Translate does. This research contributes to a broader understanding of the role AI-based translation tools play in navigating the challenges of translating culturally rich content. It also recommends that future translation technologies incorporate adaptive strategies to improve the accessibility of culturally significant terms, thereby enhancing cross-cultural communication in audiovisual media.

Wah Academia Journal of Social SciencesVol. 4(1)
University of Management and Technology (PK)
Quality Education
Openalex Percentile: Top 82%
Subtitles and Audiovisual Media
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Exploring Indian Loanwords in Netflix Subtitles: A Comparative Analysis of Google Translate and WhatsApp Meta Translator — Seemab Jamil Ghouri, Komal Zahid · Wah Academia Journal of Social Sciences (2025) | TGRS Research Map | TGRS