Exploiting discourse structure of traditional digital media to enhance automatic fake news detection
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http://hdl.handle.net/10045/112843
Título: | Exploiting discourse structure of traditional digital media to enhance automatic fake news detection |
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Autor/es: | Bonet-Jover, Alba | Piad-Morffis, Alejandro | Saquete Boró, Estela | Martínez-Barco, Patricio | García Cumbreras, Miguel Ángel |
Grupo/s de investigación o GITE: | Procesamiento del Lenguaje y Sistemas de Información (GPLSI) |
Centro, Departamento o Servicio: | Universidad de Alicante. Departamento de Lenguajes y Sistemas Informáticos |
Palabras clave: | Natural language processing | Fake news | Automated fact-checking | Deep Learning | Machine Learning | Human Language Technologies |
Área/s de conocimiento: | Lenguajes y Sistemas Informáticos |
Fecha de publicación: | 1-may-2021 |
Editor: | Elsevier |
Cita bibliográfica: | Expert Systems with Applications. 2021, 169: 114340. https://doi.org/10.1016/j.eswa.2020.114340 |
Resumen: | This paper presents a novel architecture for dealing with Automatic Fake News detection. The architecture factors in the discourse structure of news in traditional digital media and is based on two premises. First, fake news tends to mix true and false information with the purpose of confusing readers. Second, this research is focused on fake news delivered in traditional digital media, so our approach considers the influence of the journalistic structure of news, and the way journalists tend to introduce the essential content in a news story using 5W1H answer. Considering both premises, this proposal deals with the news components separately because some may be true or false, instead of considering the veracity value of the news article as a unit. A two-layer architecture is proposed, Structure and Veracity layers. To demonstrate the validity of the proposal, a new dataset was created and annotated with a new fine-grained annotation scheme (FNDeepML) that considers the different elements of the news document and their veracity. Due to the severity of the COVID-19 pandemic crisis, health is the chosen domain, and Spanish is the language used to validate the architecture, given the lack of research in this language. However, the proposal can be applied to any other language or domain. The performance of the Veracity layer of our proposal, which factors in the traditional news article structure and the 5W1H annotation, is capable of delivering a result of F1=0.807. This represents a strong improvement when compared to the baseline, which uses the whole document with a single veracity value, obtaining F1=0.605. These findings validate the suitability and effectiveness of our approach. |
Patrocinador/es: | This research work has been partially funded by Generalitat Valenciana, Spain through project “SIIA: Tecnologias del lenguaje humano para una sociedad inclusiva, igualitaria, y accesible” with grant reference PROMETEU/2018/089, by the Spanish Government through the projects RTI2018-094653-B-C22: “Modelang: Modeling the behavior of digital entities by Human Language Technologies” and RTI2018-094653-B-C21: “LIVING-LANG: Living Digital Entities by Human Language Technologies”, as well as being partially supported by a grant from the Fondo Europeo de Desarrollo Regional (FEDER). |
URI: | http://hdl.handle.net/10045/112843 |
ISSN: | 0957-4174 (Print) | 1873-6793 (Online) |
DOI: | 10.1016/j.eswa.2020.114340 |
Idioma: | eng |
Tipo: | info:eu-repo/semantics/article |
Derechos: | © 2020 Elsevier Ltd. |
Revisión científica: | si |
Versión del editor: | https://doi.org/10.1016/j.eswa.2020.114340 |
Aparece en las colecciones: | INV - GPLSI - Artículos de Revistas |
Archivos en este ítem:
Archivo | Descripción | Tamaño | Formato | |
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Bonet-Jover_etal_2021_ESWA_final.pdf | Versión final (acceso restringido) | 1,48 MB | Adobe PDF | Abrir Solicitar una copia |
Bonet-Jover_etal_2021_ESWA_accepted.pdf | Accepted Manuscript (acceso abierto) | 1,29 MB | Adobe PDF | Abrir Vista previa |
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