Foundations for AI Driven Communication Models Qualitative Analysis of Indonesian Language Adaptation E-Commerce
DOI:
https://doi.org/10.33050/italic.v3i2.798Keywords:
Language Adaptation, E-commerce Communication, AI-driven Communication Models, Customer Satisfaction, Qualitative AnalysisAbstract
In the rapidly evolving digital economy, effective communication between sellers and customers on e-commerce platforms plays a pivotal role in shaping user experience and satisfaction. This study explores the adaptation of the Indonesian language within these interactions, focusing on the linguistic styles, usage patterns, and communication challenges faced by sellers and customers. Employing a qualitative descriptive approach, data were collected from direct conversations and product descriptions on leading Indonesian e-commerce platforms. Findings reveal a dominant use of semi-formal and informal language styles, enhanced by abbreviations, emojis, and popular digital jargon, which collectively foster a sense of familiarity and responsiveness. However, balancing language standardization with the demands for fast and engaging communication remains a significant challenge. The results underline the critical need for communication models that can adapt to the dynamic nature of digital discourse while maintaining clarity and politeness. This research lays the groundwork for developing intelligent communication systems powered by artificial intelligence, which can effectively interpret and generate contextually appropriate language in e-commerce settings. The insights gained here offer valuable foundations for future work in creating AI-driven tools aimed at enhancing digital customer engagement and satisfaction through culturally and linguistically aware communication strategies.
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