A NEW METHOD FOR DETERMINING THE TRUST STATUS OF INDIVIDUALS TO EACH OTHER IN SOCIAL NETWORKS

Abstract

Social networks are a concept that has developed in recent years and have become widely used electronic environments in daily life. Social networks are modeled as graphs and problem solutions are handled graph-based. In this study, we seek to answer the questions “Does entity A trust entity B?” and “Which entity is trustworthy and which is not?” in a social network. In this study, the trust of one entity in the network towards another entity is calculated and expressed numerically. Classical trust inference algorithms eliminate paths with shortest paths, etc., which makes the found trust rate suspicious. In our method, all paths between two individuals are found and taken into account, which makes it unique. Keeping information safe from untrusted users is crucial for social network entities. The method aims to protect the privacy and confidentiality of the entities by detecting the trustworthiness of the entities. The proposed method is applied to standard social networks and the results are presented in this paper.

Keywords

• Social network analysis
• trust
• graph navigation
• trust in social network .

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