Can computer network attributes be useful for identifying low-credibility websites? A case study in Brazil

• Published in: Social network analysis and mining Vol. 14; no. 1; p. 153
• Main Authors: Couto, João M. M, Reis, Julio C. S, Benevenuto, Fabrício
• Format: Journal Article
• Language: English
• Published: Heidelberg Springer Nature B.V 07.08.2024
• Subjects: Algorithms; Certificates; Computer networks; Computer platforms; Credibility; Datasets; Developing countries; Dissemination; Domain names; Election results; Exploitation; False information; Infrastructure; LDCs; Machine learning; Misinformation; Networking; News; Political advertising; Presidential elections; Social networks; Websites; Brazil
• ISSN: 1869-5450; 1869-5469
• DOI: 10.1007/s13278-024-01330-w

Misinformation has become a global issue with impacts on various spheres of society, particularly in developing countries like Brazil. In most misinformation ecosystems, a recurring challenge is the spread of fake news through websites that closely replicate the look and function of reputable news outlets. This facilitates their dissemination, which might also involve automation, political bias, targeted ads and even the exploitation of social network algorithms in an attempt to reach niche audiences. Due to this high complexity and the rapidly evolving nature of the problem, we are just beginning to identify patterns in the various misinformation ecosystems on the Web. In this work, we extend a previous study, offering important steps towards a deeper understanding of computer networking patterns observed on Brazilian misinformation websites. These patterns emerge from various sources, including DNS records, domain registrations, TLS certificates and hosting infrastructure. Our results reveal a novel avenue through which low-credibility news websites can be distinguished from websites of credible nature.