Domain-Level Detection and Disruption of Disinformation

• URL: http://arxiv.org/abs/2205.03338v1
• Date: Fri, 6 May 2022 16:19:08 GMT
• Title: Domain-Level Detection and Disruption of Disinformation
• Authors: Elliott Waissbluth, Hany Farid, Vibhor Sehgal, Ankit Peshin, Sadia Afroz
• Abstract summary: We are awash in disinformation consisting of lies, conspiracies, and general nonsense. Although the internet is vast, the peddlers of disinformation appear to be more localized. We propose that search engines and social-media recommendation algorithms can systematically discover and demote the worst disinformation offenders.
• Score: 17.21936233574088
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: How, in 20 short years, did we go from the promise of the internet to democratize access to knowledge and make the world more understanding and enlightened, to the litany of daily horrors that is today's internet? We are awash in disinformation consisting of lies, conspiracies, and general nonsense, all with real-world implications ranging from horrific humans rights violations to threats to our democracy and global public health. Although the internet is vast, the peddlers of disinformation appear to be more localized. To this end, we describe a domain-level analysis for predicting if a domain is complicit in distributing or amplifying disinformation. This process analyzes the underlying domain content and the hyperlinking connectivity between domains to predict if a domain is peddling in disinformation. These basic insights extend to an analysis of disinformation on Telegram and Twitter. From these insights, we propose that search engines and social-media recommendation algorithms can systematically discover and demote the worst disinformation offenders, returning some trust and sanity to our online communities.

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