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Experts perception-based system to detect misinformation in health websites

2021; Elsevier BV; Volume: 152; Linguagem: Inglês

10.1016/j.patrec.2021.11.008

1872-7344

César González-Fernández, Alberto Fernández-Isabel, Isaac Martín de Diego, Rubén R. Fernández, J.F. J. Viseu Pinheiro,

Health Literacy and Information Accessibility

Misinformation is a recurring problem that has experienced a significant growth in recent years due to the rapid development of the Internet. This development has driven the emergence of websites where their content is shared without control. This is even more dangerous in the health domain, given its specific nature and the increasing number of users searching for health-related information on the Internet. For these reasons, this information should be handled with special attention. In this paper, a novel system to detect misinformation in websites related to the health domain is presented. The proposed system uses text mining techniques and visual design features to estimate the trustworthiness of the website. It has been trained using human experts’ knowledge in the selected domain and their visual perception of the website design. Promising results have been obtained during the evaluation in the experimental stage.