In this paper, we propose Signed Graph Attention Networks (SiGATs), generalizing GAT to signed networks. SiGAT incorporates graph motifs into GAT to capture two well-known theories in signed network research, i.e., balance theory and status theory. In SiGAT, motifs offer us the flexible ...
Xu K, Wu L, Wang Z, Feng Y, Witbrock M, Sheinin V (2018) Graph2seq: graph to sequence learning with attention-based neural networks. arXiv preprint arXiv:1804.00823 Xu K, Wu L, Wang Z, Yu M, Chen L, Sheinin V (2018) Exploiting rich syntactic information for semantic parsing wit...
First, we compared shortest-paths structure. Shortest paths in weighted networks refer to the least-costly route from a source node,s, to a target node,t. Typically, the length or cost of a shortest path is interpreted as a measure of communication capacity23; networks where the average shor...
To measure balance of static signed directed networks at the micro-level, we useT(G) the proportion of balanced triads in a network among all transitive triads. Table2shows that triad-level balance values are high across all static networks with an average of 0.78 (Min = 0.52, Max = 0.90...
hence learning from the existing signed relationships in a network can be used for decision making in various mining tasks. These signed networks are getting attention in recent years due to their relevance to many applications such as categorization, recommendation, and relationship discovery in variou...
Social networks have become an indispensable part of modern life. Signed networks, a class of social network with positive and negative edges, are becoming increasingly important. Many social network...
Numerous complex systems in different domains, such as traffic, medicine, and biology, can be represented as networks. Researchers in various fields have paid considerable attention on the spreading dynamic behavior in complex networks (Bucur & Iacca, 2017; Kianian & Rostamnia, 2021; Li, Fan et...
Neural NetworksJilin UniversityBy a News Reporter-Staff News Editor at Network Daily News - Current studyresults on Networks have been published. According to news reporting from Changchun, People's Republicof China, by NewsRx journalists, research stated, "Graph Neural Networks (GNNs) are an ...
(and unsurprisingly), the properties of these networks are often dissimilar. That is, how we choose to weight a network’s edges can change its graph-theoretic profile and impact how we might interpret its function. Although we remain agnostic as to which weighting scheme is superior, we note...
Community detection problem in networks has received a great deal of attention during the past decade. Most of community detection algorithms took into account only positive links, but they are not suitable for signed networks. In our work, we propose an algorithm based on random walks for commun...