Social Media and Translation: Analysis for Machine Translation Quality Assessment - Mufliharsi, Risa; Emzir, Emzir; Dewanti, Ratna (Proceedings International Conference on Sustainable Innovation (ICoSI), 2022)
Social media nowadays has been higherdegree for getting information sharing, collaboration andcommunity building. The information can be shared,disseminated and processed has presented potential issuesthat reflected social and political participation of socialmedia users. Instagram- as one of social media exploresmany features, including automated translation.However, there are many paucities in meaning the text. Toaddress the gap, this study examined and collated machinetranslation’s result of Instagram automated translationand google translation which meaning of source taken inIndonesian gossip account in Instagram as social media’smedium. The indicators of quality of translation wereanalyzed by error findings that adapted from Popovic(2018). There are five classifications used i.e. inflexionalerrors, reordering errors, omission, addition, andmistranslation. The result implied that grammarknowledge and crowdsourced used in machine had beenbetter quality than Instagram’s, (such as: tense, wordorder, etc.). Accordingly, it is necessary for Instagram asa rising social media need to improve its crowdsources