6 citations · 12 across the 11 of their papers we have counts for
5 papers · 1 filter
GraphC: Parameter-free Hierarchical Clustering of Signed Graph Networks v2
Muhieddine Shebaro, Lucas Rusnak, Martin Burtscher +1
Spectral clustering methodologies, when extended to accommodate signed graphs, have encountered notable limitations in effectively encapsulating inherent grouping relationships. Re…
Scaling Frustration Index and Corresponding Balanced State Discovery for Real Signed Graphs
Muhieddine Shebaro, Jelena Tešić
Structural balance modeling for signed graph networks presents how to model the sources of conflicts. The state-of-the-art focuses on computing the frustration index of a signed gr…
ABCD: Algorithm for Balanced Component Discovery in Signed Networks
Muhieddine Shebaro, Jelena Tešić
The largest balanced element in signed graphs plays a vital role in helping researchers understand the fundamental structure of the graph, as it reveals valuable information about…
Advances in Scaling Community Discovery Methods for Signed Graph Networks
Maria Tomasso, Lucas Rusnak, Jelena Tešić
Community detection is a common task in social network analysis (SNA) with applications in a variety of fields including medicine, criminology, and business. Despite the popularity…
Characterizing Attitudinal Network Graphs through Frustration Cloud
Lucas Rusnak, Jelena Tešić
Attitudinal Network Graphs are signed graphs where edges capture an expressed opinion; two vertices connected by an edge can be agreeable (positive) or antagonistic (negative). A s…