What is it about?

We design methods that negate the effect of SEO manipulation by removing link spam from low quality websites, and we further propose a novel method for link spam identification based upon unique linkage patterns. In doing so, we reduce traffic to unreliable news domains from search engines while maintaining traffic to credible domains. We demonstrate that unintended effects of link spam removal are limited and explore multiple avenues to mitigate these effects on both the small-scale and large-scale webgraph experiment.

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Why is it important?

The spread of unreliable news domains has had wide-reaching negative impacts on society. Our results indicate the potential of our approach to reduce the spread of misinformation and foster a more reliable online information ecosystem. We present a framework for researchers development targeted strategies that enhance search engine trustworthiness, with the ultimate goal of benefiting the broader digital community.


Empirical results have demonstrated links between manipulative SEO strategies and misinformation sources. We show that reducing the influence of link spam has knock on effects across the webgraph, affecting many types of unreliable domains and misinformation sources in particular.

Peter Carragher
Carnegie Mellon University

Read the Original

This page is a summary of: Misinformation Resilient Search Rankings with Webgraph-based Interventions, ACM Transactions on Intelligent Systems and Technology, June 2024, ACM (Association for Computing Machinery),
DOI: 10.1145/3670410.
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