Simplifying social networks via triangle-based cohesive subgraphs
Rusheng Pan, Yunhai Wang, Jiashun Sun, Hongbo Liu, Ying Zhao, Jiazhi Xia, Wei Chen
Abstract
One main challenge for simplifying node-link diagrams of large-scale social networks lies in that simplified graphs generally contain dense subgroups or cohesive subgraphs. Graph triangles quantify the solid and stable relationships that maintain cohesive subgraphs. Understanding the mechanism of triangles within cohesive subgraphs contributes to illuminating patterns of connections within social networks. However, prior works can hardly handle and visualize triangles in cohesive subgraphs. In this paper, we propose a triangle-based graph simplification approach that can filter and visualize cohesive subgraphs by leveraging a triangle-connectivity called k-truss and a force-directed algorithm. We design and implement TriGraph, a web-based visual interface that provides detailed information for exploring and analyzing social networks. Quantitive comparions with existing methods, two case studies on real-world datasets, and the feedback from domain experts demonstrate the effectiveness of TriGraph.