Affiliation:
1. Hong Kong University of Science and Technology
2. Shenzhen Institute of Computing Sciences
Abstract
Signed bipartite graphs represent relationships between two sets of entities, including both positive and negative interactions, allowing for a more comprehensive modeling of real-world networks. In this work, we focus on the detection of cohesive subgraphs in signed bipartite graphs by leveraging the concept of balanced butterflies. A balanced butterfly is a cycle of length 4 that is considered stable if it contains an even number of negative edges. We propose a novel model called the balanced (
k
, ϵ)-bitruss, which provides a concise representation of cohesive signed bipartite subgraphs while enabling control over density (
k
) and balance (ϵ). We prove that finding the largest balanced (
k
, ϵ)-bitruss is NP-hard and cannot be efficiently approximated to a significant extent. Furthermore, we extend the unsigned butterfly counting framework to efficiently compute both balanced and unbalanced butterflies. Based on this technique, we develop two greedy heuristic algorithms: one that prioritizes followers and another that focuses on balanced support ratios. Experimental results demonstrate that the greedy approach based on balanced support ratios outperforms the follower-based approach in terms of both efficiency and effectiveness.
Publisher
Association for Computing Machinery (ACM)
Subject
General Earth and Planetary Sciences,Water Science and Technology,Geography, Planning and Development
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