Journal ArticleDOI
Trust Evaluation in Online Social Networks Using Generalized Network Flow
Reads0
Chats0
TLDR
This work proposes a modified flow-based trust evaluation scheme GFTrust, in which it addresses path dependence using network flow, and model trust decay with the leakage associated with each node, to predict trust in OSNs with a high accuracy and verify its preferable properties.Abstract:
In online social networks (OSNs), to evaluate trust from one user to another indirectly connected user, the trust evidence in the trusted paths (i.e., paths built through intermediate trustful users) should be carefully treated. Some paths may overlap with each other, leading to a unique challenge of path dependence , i.e., how to aggregate the trust values of multiple dependent trusted paths. OSNs bear the characteristic of high clustering, which makes the path dependence phenomenon common. Another challenge is trust decay through propagation, i.e., how to propagate trust along a trusted path, considering the possible decay in each node. We analyze the similarity between trust propagation and network flow, and convert a trust evaluation task with path dependence and trust decay into a generalized network flow problem. We propose a modified flow-based trust evaluation scheme GFTrust , in which we address path dependence using network flow, and model trust decay with the leakage associated with each node. Experimental results, with the real social network data sets of Epinions and Advogato, demonstrate that GFTrust can predict trust in OSNs with a high accuracy, and verify its preferable properties.read more
Citations
More filters
Proceedings ArticleDOI
Attentive Group Recommendation
TL;DR: The AGREE model not only improves the group recommendation performance but also enhances the recommendation for users, especially for cold-start users that have no historical interactions individually.
Journal ArticleDOI
Understanding Graph-Based Trust Evaluation in Online Social Networks: Methodologies and Challenges
TL;DR: This article focuses on graph-based trust evaluation models in OSNs, particularly in the computer science literature, and comparatively reviews two categories of graph-simplification-based and graph-analogy-based approaches and discusses their individual problems and challenges.
Journal ArticleDOI
A Cloud-Based Trust Management Framework for Vehicular Social Networks
Xiao Chen,Liangmin Wang +1 more
TL;DR: A layered trust management mechanism that benefits from efficient use of physical resources and related capacity issues in deployment is proposed and its deployment in a VSN scenario based on a three-layer cloud computing architecture is explored.
Journal ArticleDOI
Credibility in Online Social Networks: A Survey
Majed Alrubaian,Muhammad Al-Qurishi,Atif Alamri,Mabrook Al-Rakhami,Mohammad Mehedi Hassan,Giancarlo Fortino +5 more
TL;DR: This work will attempt to provide an overall review of the credibility assessment literature over the period 2006–2017 as applied to the context of the microblogging platform, Twitter.
Journal ArticleDOI
Trust propagation algorithm based on learning automata for inferring local trust in online social networks
TL;DR: A heuristic algorithm based on learning automata, called DLATrust, for discovering reliable paths between two users and inferring the value of trust using the proposed aggregation strategy is presented.
References
More filters
Proceedings Article
A study of cross-validation and bootstrap for accuracy estimation and model selection
TL;DR: The results indicate that for real-word datasets similar to the authors', the best method to use for model selection is ten fold stratified cross validation even if computation power allows using more folds.
Book
Network Flows: Theory, Algorithms, and Applications
TL;DR: In-depth, self-contained treatments of shortest path, maximum flow, and minimum cost flow problems, including descriptions of polynomial-time algorithms for these core models are presented.
Book ChapterDOI
Introduction to Algorithms
TL;DR: This chapter provides an overview of the fundamentals of algorithms and their links to self-organization, exploration, and exploitation.
Journal ArticleDOI
Five Rules for the Evolution of Cooperation
TL;DR: Five mechanisms for the evolution of cooperation are discussed: kin selection, direct reciprocity, indirect reciprocities, network reciprocation, group selection, and group selection.
Related Papers (5)
Understanding Graph-Based Trust Evaluation in Online Social Networks: Methodologies and Challenges
Generating trusted graphs for trust evaluation in online social networks
Wenjun Jiang,Guojun Wang,Jie Wu +2 more