The impact of automatic text translation on classification of online discussions for social and cognitive presences
Arthur Barbosa, Máverick André Dionísio Ferreira, Rafael Ferreira Mello, Rafael Dueire Lins, Dragan Gašević
Abstract
This paper reports the findings of a study that measured the effectiveness of employing automatic text translation methods in automated classification of online discussion messages according to the categories of social and cognitive presences. Specifically, we examined the classification of 1,500 Portuguese and 1,747 English discussion messages using classifiers trained on the datasets before and after the application of text translation. While the English model generated, with the original and translated texts, achieved results (accuracy and Cohen’s κ) similar to those of the previously reported studies, the translation to Portuguese led to a decrease in the performance. The indicates the general viability of the proposed approach when converting the text to English. Moreover, this study highlighted the importance of different features and resources, and the limitations of the resources for Portuguese as reasons of the results obtained.