ANALYSIS OF TRANSLATION METHODS AND QUALITY OF ILLOCUTIONARY ACTS IN INSTAGRAM’S AUTOMATIC TRANSLATIONS OF @FOLKATIVE CAPTIONS

Technological advancements have led to the emergence of automatic translation engines across various platforms, including Instagram. Instagram’s automatic translation feature enables cross-language information delivery. However, its effectiveness warrants further evaluation. This study aims to describe the types of illocutionary acts found in the captions of the Instagram account @Folkative using Searle’s (1976) theory, analyze the translation methods based on Newmark’s (1988) framework, and assess translation quality in terms of readability using the model proposed by Nababan et al. (2012). Employing a descriptive qualitative method, this research analyzed 67 sentences from 20 @Folkative posts (January–February 2025) and involved 72 respondents through surveys. The results show that the most dominant illocutionary act is representatives (64%), with the presence of multiple illocutionary acts and emojis functioning as expressive cues. The most frequently used translation methods are faithful (34%) and literal (33%), indicating a strong source-language orientation (77%). The average readability score of Instagram’s automatic translations is 2.46, categorized as medium, which suggests that the translations are generally understandable but often unnatural and contain occasional errors. Overall, Instagram’s automatic translation feature is capable of conveying basic meanings functionally but remains limited in terms of linguistic flexibility and cultural adaptation. Its effectiveness depends on the alignment between language function, translation method, and the nature of social media as a space for dynamic and emotionally resonant digital communication.