Fake News Detection via English-to-Spanish Translation: Is It Really Useful?
Fecha
2021
Profesor Guía
Formato del documento
Articulo
ORCID Autor
Título de la revista
ISSN de la revista
Título del volumen
Editor
Springer
Ubicación
ISBN
ISSN
item.page.issne
item.page.doiurl
Facultad
Facultad de Ingeniería
Departamento o Escuela
Escuela de Ingenieria Civil Informatica
Determinador
Recolector
Especie
Nota general
No disponible para descarga
Resumen
Social networks are used every day to report daily events, although the information published in them many times correspond to fake news. Detecting these fake news has become a research topic that can be approached using deep learning. However, most of the current research on the topic is available only for the English language. When working on fake news detection in other languages, such as Spanish, one of the barriers is the low quantity of labeled datasets available in Spanish. Hence, we explore if it is convenient to translate an English dataset to Spanish using Statistical Machine Translation. We use the translated dataset to evaluate the accuracy of several deep learning architectures and compare the results from the translated dataset and the original dataset in fake news classification. Our results suggest that the approach is feasible, although it requires high-quality translation techniques, such as those found in the translation’s neural-based models.
Descripción
Lugar de Publicación
Auspiciador
Palabras clave
FAKE NEWS, ENGLISH-TO-SPANISH TRANSLATION, STATISTICAL MACHINE TRANSLATION, DEEP LEARNING, TWITTER