The Effect of Data Augmentation Techniques on Persian Stance Detection
- سال انتشار: 1401
- محل انتشار: مجله بین المللی ارتباطات و فناوری اطلاعات، دوره: 15، شماره: 1
- کد COI اختصاصی: JR_ITRC-15-1_007
- زبان مقاله: انگلیسی
- تعداد مشاهده: 162
نویسندگان
Department of Information Technology Management, Science and Research Branch, Islamic Azad University, Tehran, Iran
Department of Information Technology Management, Science and Research Branch, Islamic Azad University, Tehran, Iran
Central Tehran Branch, Islamic Azad University, Tehran, Iran
چکیده
The purpose of stance detection is to identify the author's stance toward a particular topic or claim. Stance detection has become a key component in applications such as fake news detection, claim validation, argument searching, and author profiling. Although significant progress has been made in stance detection in languages such as English, little attention has been paid in some other languages, including Persian. One of the main problems of research in Persian stance detection is the shortage of appropriate datasets. In this article, to address this problem, we consider data augmentation, the artificial creation of training data, which is used to conquer the shortage of datasets. In this research, we studied several methods of data augmentation such as EDA, back-translation, and merging source dataset with similar one in English language. The experimental results indicate that combining the primary data set with the translation of another dataset with similar content in another language (for example English) result in a significant improvement in the performance of the model.کلیدواژه ها
stance detection, data augmentation. fake news, datasetاطلاعات بیشتر در مورد COI
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کد COI به مفهوم کد ملی اسناد نمایه شده در سیویلیکا است و کدی یکتا و ثابت است و به همین دلیل همواره قابلیت استناد و پیگیری دارد.