Affiliations: [a] Escuela Superior de Ingeniería Mecánica y Electrica Unidad Zacatenco (ESIME Zacatenco), Instituto Politécnico Nacional, Mexico
| [b] Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas (IIMAS), Universidad Nacional Autónoma de México, Mexico
| [c] Centro de Investigación en Computación (CIC), Instituto Politécnico Nacional, Mexico
Correspondence:
[*]
Corresponding author. Helena Gómez-Adorno, Instituto de Investigaciones en Matemáticas Aplicadas y en
Sistemas (IIMAS), Universidad Nacional Autónoma de México, Mexico city, Mexico.
Tel.: +52 5518903203; E-mail: [email protected].
Abstract: We present a new resource to analyze and detect deceptive information that is present in a huge amount of news websites. Specifically, we compiled a corpus of news in the Spanish language extracted from several websites. The corpus is annotated with two labels (real and fake) for automatic fake news detection. Furthermore, the corpus also provides the category of the news, presenting a detailed analysis on vocabulary overlap among categories. Finally, we present a style-based fake news detection method. The obtained results show that the introduced corpus is an interesting resource for future research in this area.
