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

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

Licencia

URL Licencia