Computing global structural balance in large-scale signed social networks

By Giuseppe Facchetti, Giovanni Iacono, Claudio Altafini. Proceedings of the National Academy of Sciences of the United States of America, 2011

413 citations recorded by the source corpus.

Subfields: Condensed Matter Physics, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/f0f5f8bb4dcd0d4012b396ea4100bd5e5d912e86

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In Condensed Matter Physics

In Statistical and Nonlinear Physics

Citations in the corpus

Deep Network Embedding for Graph Representation Learning in Signed Networks (2019, result): “These could be explained by the previous findings in [29] and [53] that the structural balance condition is most satisfied in the Epinions network, while least satisfied in the Wiki network.”
What are higher-order networks? (2021, background): “to the colloquial rules “the friend of a friend is my friend” and “the enemy of my enemy is my friend” [179], and recent analyses of large online social networks verified that they are indeed extremely balanced [92].”
A Survey of Signed Network Mining in Social Media (2015, methodology): “Therefore the metrics based on the definition by Davis [1967] measure the number of disagreements – the number of negative links inside clusters and the number of positive links between clusters [Bansal et al. 2004; Facchetti et al. 2011; Zheng et al. 2014].”
A tutorial on modeling and analysis of dynamic social networks. Part I (2017, background): “ the enemy of my enemy is my friend [253], creates social tensions which social actors, according to balance theory, tend to resolve. Whereas structural balance is inherentto many real-world networks [11, 254, 255], classical balance theory does not explain how the system reaches the balanced state.”
Interval Bipartite Consensus of Networked Agents Associated With Signed Digraphs (2016, background): “Networks of agents associated with signed graphs are common especially in the area of social networks ([14], [15], [25], [26]), where a positive/negative weight can describe, e.”
Understanding Polarization: Meanings, Measures, and Model Evaluation (2017, background): “Although there is some recent work that returns to the original ‘all paths’ version of balance calculations (Facchetti, Iacono, and Altafini 2011), Abell (1968) made the case against longer paths being meaningful for social relationships, and in most structural balance research the fundamental unit…”
Network-based prediction of drug combinations (2019, background): “…ght the combinatorial explosion upon inspecting network relationships of multiple drug – target modules with a disease module, theories of signed networks can be of great help, such as structural balance theories 36 , reducing the number of network patterns to investigate in the human interactome.”