Bridging Social Media and Search Engines: Dredge Words and the Detection of Unreliable Domains

Proactive content moderation requires platforms to rapidly and continuously evaluate the credibility of websites. Leveraging the direct and indirect paths users follow to unreliable websites, we develop a website credibility classification and discovery system that integrates both webgraph and large-scale social media contexts. We additionally introduce the concept of dredge words—terms or phrases for which unreliable domains rank highly on search engines—and provide the first exploration of their usage on social media. Our graph neural networks that combine webgraph and social media contexts generate to state-of-the-art results in website credibility classification and significantly improves the top-k identification of unreliable domains. Additionally, we release a novel dataset of dredge words, highlighting their strong connections to both social media and online commerce platforms.

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Publication Details

Journal
Proceedings of the International AAAI Conference on Web and Social Media
Published
2025-06-07
DOI
https://doi.org/10.1609/icwsm.v19i1.35917
Primary Topic
Spam and Phishing Detection
Type
article
Field-Weighted Citation Impact
0.00

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article

Bridging Social Media and Search Engines: Dredge Words and the Detection of Unreliable Domains

Evan Williams, Peter Carragher, Kathleen M. Carley
Proceedings of the International AAAI Conference on Web and Social Media
Spam and Phishing Detection
article

Bridging Social Media and Search Engines: Dredge Words and the Detection of Unreliable Domains

Evan Williams, Peter Carragher, Kathleen M. Carley
article en

Abstract

Proactive content moderation requires platforms to rapidly and continuously evaluate the credibility of websites. Leveraging the direct and indirect paths users follow to unreliable websites, we develop a website credibility classification and discovery system that integrates both webgraph and large-scale social media contexts. We additionally introduce the concept of dredge words—terms or phrases for which unreliable domains rank highly on search engines—and provide the first exploration of their usage on social media. Our graph neural networks that combine webgraph and social media contexts generate to state-of-the-art results in website credibility classification and significantly improves the top-k identification of unreliable domains. Additionally, we release a novel dataset of dredge words, highlighting their strong connections to both social media and online commerce platforms.

Proceedings of the International AAAI Conference on Web and Social MediaVol. 19
Carnegie Mellon University (US)
John S. and James L. Knight Foundation, Carnegie Mellon University, Office of Naval Research
Openalex Percentile: Top 82%
Spam and Phishing Detection
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Bridging Social Media and Search Engines: Dredge Words and the Detection of Unreliable Domains — Evan Williams, Peter Carragher, et al. · Proceedings of the International AAAI Conference on Web and Social Media (2025) | TGRS Research Map | TGRS