Testing structural balance theories in heterogeneous signed networks

Abstract

The abundance of data about social relationships allows the human behavior to be analyzed as any other natural phenomenon. Here we focus on balance theory, stating that social actors tend to avoid establishing cycles with an odd number of negative links. This statement, however, can be supported only after a comparison with a benchmark. Since the existing ones disregard actors' heterogeneity, we extend Exponential Random Graphs to signed networks with both global and local constraints and employ them to assess the significance of empirical unbalanced patterns. We find that the nature of balance crucially depends on the null model: while homogeneous benchmarks favor the weak balance theory, according to which only triangles with one negative link should be under-represented, heterogeneous benchmarks favor the strong balance theory, according to which also triangles with all negative links should be under-represented. Biological networks, instead, display strong frustration under any benchmark, confirming that structural balance inherently characterizes social networks.

46 pages, 14 figures, 7 tables

References in corpus (7)

• Multirelational Organization of Large-scale Social Networks in an Online World
• Social Balance on Networks: The Dynamics of Friendship and Enmity
• Analysis of community structure in networks of correlated data
• Maximum likelihood: extracting unbiased information from complex networks
• Fast and scalable likelihood maximization for Exponential Random Graph Models with local constraints
• Polarization and multiscale structural balance in signed networks
• Detecting mesoscale structures by surprise

Cited by in corpus (6)

• Echo chamber effects in signed networks
• Assessing frustration in real-world signed networks: a statistical theory of balance
• Patterns of link reciprocity in directed, signed networks
• Statistically validated projection of bipartite signed networks
• Assessing imbalance in signed brain networks
• Heider balance on Archimedean lattices and cliques