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.

由于互联网的快速发展，错误信息是一个反复出现的问题，近年来出现了显着增长。这一发展推动了网站的出现，在这些网站中，其内容不受控制地共享。鉴于其特定性质以及在 Internet 上搜索与健康相关的信息的用户数量不断增加，这在健康领域中更加危险。由于这些原因，应特别注意处理这些信息。在本文中，提出了一种新的系统来检测与健康领域相关的网站中的错误信息。所提出的系统使用文本挖掘技术和视觉设计特征来估计网站的可信度。它已经使用人类专家在所选领域的知识及其对网站设计的视觉感知进行了培训。