References

Relevance of language in detecting unreliable content:

• Lugea, J. (2021). Linguistic approaches to fake news detection. Data science for fake news: Surveys and perspectives, 287-302.

• Horne, B., & Adali, S. (2017). This just in: Fake news packs a lot in title, uses simpler, repetitive content in text body, more similar to satire than real news. In Proceedings of the international AAAI conference on web and social media (Vol. 11, No. 1, pp. 759-766).

5W1H technique as a way to identify relevant content in news:

• Zhang, H., Chen, X., & Ma, S. (2019, November). Dynamic news recommendation with hierarchical attention network. In 2019 IEEE International Conference on Data Mining (ICDM) (pp. 1456-1461). IEEE.

Annotation scheme used to annotate the corpus:

• Bonet-Jover, A., Sepúlveda-Torres, R., Saquete, E., Martínez-Barco, P., & Nieto-Pérez, M. (2023). RUN-AS: a novel approach to annotate news reliability for disinformation detection. Language Resources and Evaluation, 1-31.

A subset of news used in this task was collected from the corpus presented in the FakeDeS Task at Iberlef 2021: 

• Posadas-Durán, J. P., Gómez-Adorno, H., Sidorov, G., & Escobar, J. J. M. (2019). Detection of fake news in a new corpus for the Spanish language. Journal of Intelligent & Fuzzy Systems, 36(5), 4869-4876.

Evaluation metrics:

• Piad-Morffis, A., Gutiérrez, Y., Canizares-Diaz, H., Estevez-Velarde, S., Muñoz, R., Montoyo, A., & Almeida-Cruz, Y. (2020). Overview of the ehealth knowledge discovery challenge at iberlef 2020.