Social Media and Translation: Analysis for Machine Translation Quality Assessment
Prosiding International Conference on Sustainable Innovation (ICoSI),
Vol. 2 No. 2 (2022): Optimizing Global Benefit for Future Wellbeing
Abstract
Social media nowadays has been higher
degree for getting information sharing, collaboration and
community building. The information can be shared,
disseminated and processed has presented potential issues
that reflected social and political participation of social
media users. Instagram- as one of social media explores
many features, including automated translation.
However, there are many paucities in meaning the text. To
address the gap, this study examined and collated machine
translation’s result of Instagram automated translation
and google translation which meaning of source taken in
Indonesian gossip account in Instagram as social media’s
medium. The indicators of quality of translation were
analyzed by error findings that adapted from Popovic
(2018). There are five classifications used i.e. inflexional
errors, reordering errors, omission, addition, and
mistranslation. The result implied that grammar
knowledge and crowdsourced used in machine had been
better quality than Instagram’s, (such as: tense, word
order, etc.). Accordingly, it is necessary for Instagram as
a rising social media need to improve its crowdsources
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