Modeling Predictors of Accuracy in Web-Translated Newspaper Stories

Abstract

Recently, newspapers published in Africa began to adopt web translation applications to make their businesses more competitive. However, studies indicate that web translations of even major languages are often inaccurate and generally gloss over how this affects African languages. And the predictors of translation inaccuracy seem to be inadequately interrogated. This study, therefore, investigates the extent to which Google Translate accurately translates English to eight African languages and the relationship between translation accuracy and perceived journalistic errors, orthography and technological limitations of the translating machine. Through document analysis of six newspaper stories, the study ascertained that the meaning of over 45% of the text was either lost or unclear. Statistical analysis shows that perceived journalistic errors, inadequate orthography and technological limitations significantly predict translation inaccuracy, suggesting that improvement in these variables would improve the accuracy of web-translated news.