Multi-relational reinforcement for computing credibility of nodes

Hu, Weishu; Gong, Zhiguo

doi:10.1007/s11280-015-0375-8

Cited by 2 publications

(1 citation statement)

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“…In the current article, the concept of similarity is considered to assess the value of the users' credibility. In this domain, some researches used the users' similarity concept in order to estimate their credibility and then concluded that popular users have a higher credibility score [60], [61]. In addition, they found that there is a direct relationship between the users' ranks and their credibility values.…”

Section: ) Ranking Scores Verification Based On the Credibilitymentioning

confidence: 99%

Consensus Opinion Model in Online Social Networks Based on Influential Users

2019

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A framework to consensus opinion model within a networked social group is put forward. The current research in opinion formation within the groups is largely based on the opinion aggregation of each user of the network. However, the consistency of users in aggregation, social power, and the impact of each individual user of the group for opinion formation are not considered. In this paper, we investigate a consensus opinion model in social groups based on the impact of influential users and aggregation methods. In order to reach the consensus model, we aggregate the users' opinions. To maintain consistency, we propagate the opinion through the users to reach an agreement. This propagation will consider the influential users' impacts that have a crucial effect on its process. A novel method is proposed to detect the influential users and opinion propagation based on them to derive the opinion toward the networked social group. In particular, we applied optimism and pessimism scores as the users' personality to discover the influential users in the network. Considering that, we propagate the opinion based on two facts: 1) the impact of influential users, derived by the presence of an extremely confident individual in the network and 2) the impact of neighbors, induced by the presence of the users who have a connection with the current user. Then, we proposed the opinion aggregation of the group induced by the weighted averaging operator and fuzzy techniques. In order to evaluate the validity of the method, we used enormous data sets of Epinions and Etsy which are signed and unsigned, respectively. INDEX TERMS Influential users, link analysis, opinion propagation, voter model, fuzzy methods, consensus model, online social networks. I. INTRODUCTION The online social networks (OSN) are growing and penetrating the people lives such that almost every person in the world has a membership at least in one of them. A user may refer to the web to get information about TV, songs, movie tickets, jobs, or even mates. As these decisions and the fundamental financial processes move to the web, there is growing economic inspiration to propagate opinion through the web. Social networking websites have facilitated a new style of communication and opinion propagation through the links between their users. Today, a tremendous amount of users take part in different social networks such as eBay, Twitter, Amazon, Facebook, Alibaba etc. and create many social links with other users of that network. The networks of interest are online shopping centers in which the websites provide product for users. In order to recommend a product or prepare The associate editor coordinating the review of this manuscript and approving it for publication was Zhan Bu.

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Section: ) Ranking Scores Verification Based On the Credibilitymentioning

confidence: 99%