This paper studies the novel problem of influence-based community deception. Tackling this problem amounts to devising tools to protect the users of a community from being discovered by community detection algorithms. The novel setting considers networks that have both edge directions and models the influence of nodes as edge weights. We present a deception strategy based on modularity. We conducted an experimental evaluation that shows the feasibility of our proposal.
Influence-Based Community Deception
Pirrò, Giuseppe
2023-01-01
Abstract
This paper studies the novel problem of influence-based community deception. Tackling this problem amounts to devising tools to protect the users of a community from being discovered by community detection algorithms. The novel setting considers networks that have both edge directions and models the influence of nodes as edge weights. We present a deception strategy based on modularity. We conducted an experimental evaluation that shows the feasibility of our proposal.File in questo prodotto:
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