A Credibility-Based Analysis of Information Diffusion in Social Networks

Social networks have many advantages and they are very popular. The number of people having at least one account on a certain social network has grown considerably. Social networks allow people to connect and interact more easily with one another, leading to a much easier way to obtain information. However one major disadvantage of social networks is that some information may be untrue. In this paper we propose a protocol in which the network becomes more immune to the diffusion of false information. Our approach is based on evidence theory with Dempster-Shafer and Yager's rule which plays an important role in an individual's decision whether to send further the received information or not. We also took into consideration the confidence degree of the neighbours regarding the information which is spread by a specific source node. Furthermore, we propose a simulation algorithm that allows us to observe the diffusion of two contradictory information spread by two different source nodes. The experimental results show that the true information spreads more easily if the ground truth is sometimes revealed, even rarely.