Improving Recommendation Flow with Centrality Measure in an Evolving Social Network

The purpose of our research is to make a connection between information related to structural position of entities and individual advice selection criteria in an explicitly mentioned friendship or trust network of users. We provide a reliable mechanism in which users are able to cover most of the related information available matched with their preferences by going further to the network. We showed in our model that structural position of the network can be treated as a useful source of information by improving flow of information in the system. Finally we have implemented our model as a trust-based exchange mechanism for advice selection in Net Logo. As the results show, by embedding such information we are able to increase the utility of entities and overall utility of the system.