Relaxed Clique Percolation and Disinformation-Resilient Domains for Social Commerce Networks
Himangshu Paul, Alexander Nikolaev

TL;DR
This paper introduces a novel method called Relaxed Clique Percolation to create disinformation-resilient domains in social networks, leveraging social link structures without needing to identify malicious nodes explicitly.
Contribution
The paper proposes the RCP approach for forming resilient social network domains, enabling personalized content aggregation that mitigates disinformation risks without prior node classification.
Findings
RCP domains are large and spatially diverse in real-world networks.
RCP cores enable efficient composition of resilient domains for all nodes.
The approach reduces disinformation spread without explicit malicious node detection.
Abstract
Must we trace and block all fake content in a social commerce network so that genuine users may enjoy fake-free information? Such efforts largely fail, because, as we get better at spam detection, spammers use the same advances for anti-detection. As a fundamentally new approach, we show that an online platform can aggregate and route user-generated content in a smart personalized way, which fosters and relies on "collective social responsibility". We introduce the notion of information aggregation domain, or simply, domain: composed for a given "central" node (user account), a domain is a connected set of nodes whose user-generated content is eligible to be used to meet the central node's information needs. Admitting malicious information sources - "bad citizen" nodes - into "good citizen" nodes' domains puts the good citizens at risk for disinformation attacks. We show how a platform…
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Taxonomy
TopicsSpam and Phishing Detection · Complex Network Analysis Techniques · Privacy-Preserving Technologies in Data
