Structural balance theory affirms that signed social networks, i.e., graphs whose signed edges represent friendly/hostile interactions among individuals, tend to be organized so as to avoid conflictual situations, corresponding to cycles of negative parity. Using an algorithm for ground state calculation in large-scale Ising spin glasses, in this paper we compute the global level of balance of very large on-line social networks, and verify that currently available networks are indeed extremely balanced. This property is explainable in terms of the high degree of skewness of the sign distributions on the nodes of the graph. In particular, individuals linked by a large majority of negative edges create mostly ``apparent disorder'', rather ...
Inconsistencies in the empirical support for balance theory are often explained by recourse to compe...
This paper presents a game-theoretic approach that models the formation of signed networks which con...
Abstract: Previous studies on social networks are often focused on networks with only positive relat...
Analogously to a spin glass, a large-scale signed social network is characterized by the presence of...
There is a longstanding belief that in social networks with simultaneous friendly and hostile intera...
We present measures, models and link prediction algorithms based on the structural balance in signed...
There is a longstanding belief that in social networks with simultaneous friendly and hostile intera...
| openaire: EC/H2020/654024/EU//SoBigDataSigned networks are graphs whose edges are labelled with ei...
Structural balance modeling for signed graph networks presents how to model the sources of conflicts...
The study of social networks is a burgeoning research area. However, most existing work is on networ...
The study of social networks is a burgeoning research area. However, most existing work is on networ...
Signed networks have long been used to represent social relations of amity (+) and enmity (-) betwee...
Network visualization has established as a key complement to network analysis since the large variet...
Statistical network models are useful for understanding the underlying formation mechanism and chara...
The paper presents results derived from a series of simulations of signed networks (i.e., networks c...
Inconsistencies in the empirical support for balance theory are often explained by recourse to compe...
This paper presents a game-theoretic approach that models the formation of signed networks which con...
Abstract: Previous studies on social networks are often focused on networks with only positive relat...
Analogously to a spin glass, a large-scale signed social network is characterized by the presence of...
There is a longstanding belief that in social networks with simultaneous friendly and hostile intera...
We present measures, models and link prediction algorithms based on the structural balance in signed...
There is a longstanding belief that in social networks with simultaneous friendly and hostile intera...
| openaire: EC/H2020/654024/EU//SoBigDataSigned networks are graphs whose edges are labelled with ei...
Structural balance modeling for signed graph networks presents how to model the sources of conflicts...
The study of social networks is a burgeoning research area. However, most existing work is on networ...
The study of social networks is a burgeoning research area. However, most existing work is on networ...
Signed networks have long been used to represent social relations of amity (+) and enmity (-) betwee...
Network visualization has established as a key complement to network analysis since the large variet...
Statistical network models are useful for understanding the underlying formation mechanism and chara...
The paper presents results derived from a series of simulations of signed networks (i.e., networks c...
Inconsistencies in the empirical support for balance theory are often explained by recourse to compe...
This paper presents a game-theoretic approach that models the formation of signed networks which con...
Abstract: Previous studies on social networks are often focused on networks with only positive relat...