Calculating the Maximum Trust in Online Social Networks Using Genetic Algorithm and Ant Colony Optimization

The interaction between social network users plays an important role in analyzing the properties of social networks. Calculating the trust and the trust route is one of the most important concepts in Social Network Analysis (SNA) which highly affects the interconnections, decisions, and interactions among the users in e-commerce or recommendation systems. This concept and related calculation method depend on the structure and parameters of the network and the attributes of the users. In this paper, a new method is proposed for calculating themaximum trust and the trust route between any two users of a social network having a structure similar to Facebook, and due to the NP-Hard complexity of the problem, two metaheuristic approaches based on Genetic Algorithm (GA) and Ant Colony Optimization (ACO) are developed. The proposed methods are simulated in Matlab over 6 different test cases adopted from Facebook data-set and the maximumtrust between two users is calculated. The computational results show that the trust value obtained by GA and ACO algorithms are almost similar, but the GA approach performs faster than the ACO as the size of the network increases.

Keywords:

Online Social Network Analysis , Maximum Trust , Trust Route , Genetic Algorithm , Ant Colony Optimization