Characterizing Low Credibility Websites in Brazil through Computer Networking Attributes

• Published in: 2022 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) pp. 42 - 46
• Main Authors: Couto, Joao M. M., Reis, Julio C. S., Cunha, Italo, Araujo, Leandro, Benevenuto, Fabricio
• Format: Conference Proceeding
• Language: English
• Published: IEEE 10.11.2022
• Subjects: Automation; Brazilian Websites; Complexity theory; Computer Network Attributes; Credibility; Ecosystems; Fake news; Gears; Geology; Machine learning; Misinformation; Social networking (online)
• DOI: 10.1109/ASONAM55673.2022.10068660

A key gear in most misinformation ecosystems is the deployment of fake news web sites that publish news in a similar fashion to how news articles are put out by credible sources. The content offered by these sites is disseminated in a complex process that may involve automation, exploitation of message apps and social network algorithms, political bias, and targeted ads to reach large and niche audiences. Due to this high complexity and the rapidly evolving nature of the problem, we are just beginning to understand patterns in the various misinformation ecosystems on the Web. In this work, we offer a first step towards understanding network properties, including data from DNS records, domain registration, TLS certificates, and hosting infrastructure of Brazilian web sites associated with the dissemination of misinformation content on digital platforms. Our findings, in addition to providing a better understanding of the misinformation ecosystem in Brazil, also reveal a novel set of features useful to distinguish low credibility web sites from others.