Trusted Social Node: Evaluating the Effect of Trust and Trust Variance to Maximize Social Influence in a Multilevel Social Node Influential Diffusion Model

The use of social networking sites has been very successful on large-scale information sharing. Hence, a vast proposed application possibilities for different people and organizations emerged. Although the use of social networking sites nowadays for large scale information sharing and the spreading of messages on these platforms is considerably effective, this research hypothesizes that trust is able to increase the rate of successfully influenced social nodes. Trust is the fundamental motivation that people cooperates towards a common purpose. This paper discusses trust - a measure of belief and disbelief using experimental simulation to evaluate and compare on the rate of successfully influenced social nodes based on the Trusted Social Node (TSN). This paper considers trust variance and social node impact factor in the Genetic Algorithm Diffusion Model (GADM) to analyze on its successful influential rate with and without the presence of trust in the algorithm. Results produced are a set of influential diffusion time graph where the graph shows there are incremental rate of successfully influenced social nodes with the presence of trust metrics.