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相关论文: Balance and Frustration in Signed Networks

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We analyse signed networks from the perspective of balance theory which predicts structural balance as a global structure for signed social networks that represent groups of friends and enemies. The scarcity of balanced networks encouraged…

社会与信息网络 · 计算机科学 2019-01-23 Samin Aref

Computing the frustration index of a signed graph is a key step toward solving problems in many fields including social networks, political science, physics, chemistry, and biology. The frustration index determines the distance of a network…

社会与信息网络 · 计算机科学 2019-08-27 Samin Aref , Andrew J. Mason , Mark C. Wilson

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 signed graph is called balanced if each of its cycles…

社会与信息网络 · 计算机科学 2021-10-15 Lucas Rusnak , Jelena Tešić

Signed networks with positive and negative interaction are widely observed in the real systems. The negative links would induce frustration, then affect global properties of the system. Based on previous studies, frustration of signed…

统计力学 · 物理学 2018-10-25 Jiayu Cao , Ying Fan , Zengru Di

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 graph, a critical step toward solving problems in social and…

社会与信息网络 · 计算机科学 2025-01-16 Muhieddine Shebaro , Jelena Tešić

Most of the analyses concerning signed networks have focused on the balance theory, hence identifying frustration with undirected, triadic motifs having an odd number of negative edges; much less attention has been paid to their directed…

物理与社会 · 物理学 2025-04-07 Anna Gallo , Fabio Saracco , Renaud Lambiotte , Diego Garlaschelli , Tiziano Squartini

We consider signed networks in which connections or edges can be either positive (friendship, trust, alliance) or negative (dislike, distrust, conflict). Early literature in graph theory theorized that such networks should display…

社会与信息网络 · 计算机科学 2019-01-30 Alec Kirkley , George T. Cantwell , M. E. J. Newman

Signed networks provide a principled framework for representing systems in which interactions are not merely present or absent but qualitatively distinct: friendly or antagonistic, supportive or conflicting, excitatory or inhibitory. This…

Is the enemy of an enemy necessarily a friend? If not, to what extent does this tend to hold? Such questions were formulated in terms of signed (social) networks and necessary and sufficient conditions for a network to be "balanced" were…

社会与信息网络 · 计算机科学 2018-08-21 Samin Aref , Mark C. Wilson

According to the so-called strong version of structural balance theory, actors in signed social networks avoid establishing triads with an odd number of negative links. Generalising, the weak version of balance theory allows for nodes to be…

物理与社会 · 物理学 2024-12-23 Anna Gallo , Diego Garlaschelli , Tiziano Squartini

For the signed graph associated to a deep neural network, one can compute the frustration level, i.e., test how close or distant the graph is to structural balance. For all the pretrained deep convolutional neural networks we consider, we…

机器学习 · 计算机科学 2025-10-08 Joel Wendin , Erik G. Larsson , Claudio Altafini

We present measures, models and link prediction algorithms based on the structural balance in signed social networks. Certain social networks contain, in addition to the usual 'friend' links, 'enemy' links. These networks are called signed…

社会与信息网络 · 计算机科学 2014-02-28 Jérôme Kunegis

Signed networks appear naturally in contexts where conflict or animosity is apparent. In this book chapter we review some of the literature on signed networks, especially in the context of partitioning. Most of the work is founded in what…

物理与社会 · 物理学 2018-03-07 V. A. Traag , P. Doreian , A. Mrvar

Statistical network models are useful for understanding the underlying formation mechanism and characteristics of complex networks. However, statistical models for \textit{signed networks} have been largely unexplored. In signed networks,…

统计方法学 · 统计学 2023-09-04 Weijing Tang , Ji Zhu

An important measure of signed graphs is the line index of balance which has several applications in many fields. However, this graph-theoretic measure was underused for decades because of the inherent complexity in its computation which is…

社会与信息网络 · 计算机科学 2018-02-08 Samin Aref , Andrew J. Mason , Mark C. Wilson

In signed networks, each edge is labeled as either positive or negative. The edge sign captures the polarity of a relationship. Balance of signed networks is a well-studied property in graph theory. In a balanced (sub)graph, the vertices…

社会与信息网络 · 计算机科学 2020-10-22 Kartik Sharma , Iqra Altaf Gillani , Sourav Medya , Sayan Ranu , Amitabha Bagchi

The study of social networks is a burgeoning research area. However, most existing work deals with networks that simply encode whether relationships exist or not. In contrast, relationships in signed networks can be positive ("like",…

社会与信息网络 · 计算机科学 2013-03-06 Kai-Yang Chiang , Cho-Jui Hsieh , Nagarajan Natarajan , Ambuj Tewari , Inderjit S. Dhillon

There is a long-standing belief that in social networks with simultaneous friendly/hostile interactions (signed networks) there is a general tendency to a global balance. Balance represents a state of the network with lack of contentious…

物理与社会 · 物理学 2014-06-10 Ernesto Estrada , Michele Benzi

Two competing types of interactions often play an important part in shaping system behavior, such as activatory or inhibitory functions in biological systems. Hence, signed networks, where each connection can be either positive or negative,…

社会与信息网络 · 计算机科学 2024-01-09 Yu Tian , Renaud Lambiotte

Alliances and conflicts in social, political and economic relations can be represented by positive and negative edges in signed networks. A cycle is said to be positive if the product of its edge signs is positive, otherwise it is negative.…

物理与社会 · 物理学 2024-08-13 Fernando Diaz-Diaz , Paolo Bartesaghi , Ernesto Estrada
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