Results 11 to 20 of about 84,342 (259)
Balance and frustration in signed networks [PDF]
Journal of Complex Networks, 2018 The frustration index is a key measure for analysing signed networks, which has been underused due to its computational complexity. We use an exact optimisation-based method to analyse frustration as a global structural property of signed networks coming from diverse application areas.
Samin Aref, Mark C. Wilson
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Signed networks in social media [PDF]
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 2010 Relations between users on social media sites often reflect a mixture of positive (friendly) and negative (antagonistic) interactions. In contrast to the bulk of research on social networks that has focused almost exclusively on positive interpretations of links between people, we study how the interplay between positive and negative relationships ...
Jure Leskovec +2 more
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Dynamics over Signed Networks [PDF]
SIAM Review, 2019 In press, SIAM ...
Shi, Guodong +2 more
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Bipartite Consensus Problems on Second-Order Signed Networks With Heterogeneous Topologies
IEEE Access, 2020 This paper is devoted to the convergence problem for second-order signed networks that are associated with two signed graphs in the presence of heterogeneous topologies.
Jianheng Ling +2 more
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Physical Review E, 2019 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 "structural balance," meaning that certain configurations of positive and negative edges are favored and others are ...
Alec Kirkley +2 more
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Link prediction in multiplex online social networks [PDF]
Royal Society Open Science, 2017 Online social networks play a major role in modern societies, and they have shaped the way social relationships evolve. Link prediction in social networks has many potential applications such as recommending new items to users, friendship suggestion and ...
Mahdi Jalili +4 more
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CoRR, 2018 To appear as a chapter in "Advances in Network Clustering and Blockmodeling" edited by P. Doreian, V. Batagelj & A. Ferligoj (Wiley, New York, 2018)
Vincent A. Traag +2 more
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Enhanced Signed Graph Neural Network with Node Polarity
Entropy, 2022 Signed graph neural networks learn low-dimensional representations for nodes in signed networks with positive and negative links, which helps with many downstream tasks like link prediction.
Jiawang Chen +3 more
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Signed Graph Convolutional Networks
2018 IEEE International Conference on Data Mining (ICDM), 2018 Due to the fact much of today's data can be represented as graphs, there has been a demand for generalizing neural network models for graph data. One recent direction that has shown fruitful results, and therefore growing interest, is the usage of graph convolutional neural networks (GCNs). They have been shown to provide a significant improvement on a
Tyler Derr, Yao Ma 0001, Jiliang Tang
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Delineating Changes in the Fundamental Structure of Signed Networks
Frontiers in Physics, 2020 We tackle two problems. One is understanding parts of the operation of the US Supreme Court. The other is a fundamental problem for network analysis. It is delineating the fundamental structures of networks.
Patrick Doreian +2 more
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