Exploring Indian Loanwords in Netflix Subtitles: A Comparative Analysis of Google Translate and WhatsApp Meta Translator - Seemab Jamil Ghouri; Ayesha Tariq; Komal Zahid (Wah Academia Journal of Social Sciences, 2025)
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.