A Context-Aware Multi-Faceted Trust and Distrust Model for Online Social Networks

Today, online social networks (OSNs) have gained an important role in everyday human life. With the ever Increasing use of different types of OSNs as well as the extension of social interactions, the role of trust has become significantly more important. The success of the social network depends on the correct analysis of social situations, interactions and applying appropriate approaches according to each specific situation. Trust and distrust are two considerable factors to analyze these networks. The main purpose of this research has been to improve the accuracy of calculating trust and distrust based on the theoretical foundation of social interactions as well as the decision making in the social environment. By reviewing the body of literature in the fields of sociology and psychology focusing on trust and distrust in the social environments, we have concluded that distrust information, as well as trust, plays an important role in social interactions and decision making. The construct of trust and distrust are independent but they affect one another. This independent identity means that they are counting on the basis of the attributes and related factors. The aim of this research has been to model the co-existence of trust and distrust in maintaining the independence of each identity while considering different criteria for each of them. Based on the theorem of subjective logic we have modeled the coexistence of trust and distrust. So far, the existing models have only focused on trust information and its corresponding calculations. There are other works that have focused on distrust Information. But, in these models, distrust information has been gathered directly by users or calculated based on trust information sources. Therefore, in this research, we have proposed the calculation of trust and distrust based on individual and entangled trust and distrust formation factors. These factors are used in the decision making process. The results of the performed evaluations demonstrate that the proposed model has generated more accurate outcomes in calculating trust and distrust within a trust-based decision making context compared to other existing models.