The impact of automatic text translation on classification of online discussions for social and cognitive presences

被引:12
作者
Barbosa, Arthur [1 ]
Ferreira, Maverick [2 ]
Mello, Rafael Ferreira [1 ]
Lins, Rafael Dueire [1 ]
Gasevic, Dragan [3 ]
机构
[1] Univ Fed Rural Pernambuco, Recife, PE, Brazil
[2] Univ Fed Pernambuco, Recife, PE, Brazil
[3] Monash Univ, Clayton, Vic, Australia
来源
LAK21 CONFERENCE PROCEEDINGS: THE ELEVENTH INTERNATIONAL CONFERENCE ON LEARNING ANALYTICS & KNOWLEDGE | 2021年
关键词
Community of Inquiry Model; Content Analytics; Online Discussion; Text Translation; COHESION;
D O I
10.1145/3448139.3448147
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
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.) 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.
引用
收藏
页码:77 / 87
页数:11
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