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On the Network Embedding in Sparse Signed Networks
2019Network embedding, that learns low-dimensional node representations in a graph such that the network structure is preserved, has gained significant attention in recent years. Most state-of-the-art embedding methods have mainly designed algorithms for representing nodes in unsigned social networks.
Ayan Kumar Bhowmick +2 more
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Laplacian dynamics on signed networks
2016 IEEE 55th Conference on Decision and Control (CDC), 2016In this paper, we examine the properties of the Laplacian matrix defined on signed networks, referred to as the signed Laplacian matrix, from a graph-theoretic perspective. The connection between the stability of the signed Laplacian with the cut set of the network is established. This is then followed by relating and the number of negative eigenvalues
Lulu Pan, Haibin Shao, Mehran Mesbahi
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Prediction in signed heterogeneous networks
Proceedings of the 2014 IEEE 18th International Conference on Computer Supported Cooperative Work in Design (CSCWD), 2014The problem of prediction is an important task in network analysis, which has attracted more attention from computer science communities. In this paper, prediction in signed heterogeneous networks is addressed, which contains two aspects, link prediction and sign prediction.
Li Pan +3 more
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Social balance in signed networks
Information Systems Frontiers, 2014The theory of social balance, also called structural balance, is first proposed by Heider in 1940s, which is utilized to describe the potential social dynamics process. This theory is of great importance in sociology, computer science, psychology and other disciplines where social systems can be represented as signed networks.
Xiaolong Zheng 0001 +2 more
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Modelling weighted signed networks
2019In this paper we introduce a new modelling approach to analyse weighted signed networks by assuming that their generative process consists of two models: the interaction model which describes the overall connectivity structure of the relations in the network without taking into account neither the weight nor the sign of the dyadic relations; and the ...
Caimo, Alberto, Gollini, Isabella
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Single Sign-on and Social Networks
IEEE Distributed Systems Online, 2008Call it what you will - single sign-on, federated identity, one-stop authentication - letting users sign on to the Internet once and securely access network resources anywhere has been one of the industry's enduring quests.
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Attributed Signed Network Embedding
Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017The major task of network embedding is to learn low-dimensional vector representations of social-network nodes. It facilitates many analytical tasks such as link prediction and node clustering and thus has attracted increasing attention. The majority of existing embedding algorithms are designed for unsigned social networks.
Suhang Wang +3 more
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DSP: Deep Sign Prediction in Signed Social Networks
2020In a signed social network, users can express emotional tendencies such as: like/dislike, friend/foe, support/oppose, trust/distrust to others. Sign prediction, which aims to predict the sign of an edge, is an important task of signed social networks. In this paper, we attempt to tackle the problem of sign prediction by proposing a Deep Sign Prediction
Wei Yang, Yitong Wang, Xinshu Li
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Signed Clique Search in Signed Networks: Concepts and Algorithms
IEEE Transactions on Knowledge and Data Engineering, 2019Mining cohesive subgraphs from a network is a fundamental problem in network analysis. Most existing cohesive subgraph models are mainly tailored to unsigned networks. In this paper, we study the problem of seeking cohesive subgraphs in a signed network, in which each edge can be positive or negative, denoting friendship or conflict, respectively.
Rong-Hua Li +6 more
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Recommendations in Signed Social Networks
Proceedings of the 25th International Conference on World Wide Web, 2016Recommender systems play a crucial role in mitigating the information overload problem in social media by suggesting relevant information to users. The popularity of pervasively available social activities for social media users has encouraged a large body of literature on exploiting social networks for recommendation.
Jiliang Tang +2 more
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