Product Analysis of Google Translate Into Netspeak id_ID

Abstract

This study aims to examine the accuracy of instant translation of Netspeak  since the Google translate system has inevitably replaced the human translator. This study investigated two aspects, namely (1) the types of slang words that are commonly posted by the most popular English-speaking Instagram celebrities, and (2) the translation shift of the translated posts from English into Indonesian using Google Translate app. Halliday’s transitivity process and Baker’s translation strategies are used as theoretical framework to obtain the data. This study employed qualitative approach using content analysis. The data were obtained from popular Instagram posts on 5 themes: culinary, fashion, lifestyle, mental health, and tourism. Clauses from the posts that contain slang words were classified based on the relationship among participants, process, and circumstance. The result showed that Google translate can be used as a supporting instrument in the translation process. Nevertheless, the human translators are required in the last stage to convey a closer meaning to the source text.