Semantic Analysis In Online Social Network And Construction Of Semantic Social Networking

Online social networking systems have gained great success in recent years. In this paper, we will analyze the semantic information in online social networks, and discuss the necessity and possibility of introducing semantics into online social networking.We will do analysis on the current lightweight semantics in online social networks-tag, by measuring its semantic relatedness, network characteristics, etc, and thus form the base for semantic social networking. We propose to model the tags data as a folksonomy network and find it has the properties of scale-free network and small world network, and thus demonstrate the semantic stability of tagging behavior. We use the method of both co-occurrence and resource context to construct 5 folksonomy networks, and then apply different relatedness measurement methods to measure the semantic similarity of these networks. The experiment shows that although the formation methods are different, the experiment result are consisted with each other. This kind of semantic relatedness could be applied in many aspects, such as text keyword generation as shown in this paper.We realize that the lack of semantics causes the problems of data inconsistence, un-stable description, etc. These problems hinder the further development of online social network applications. As a result, we try to bring the semantic framework and method into online social network. We setup the semantic model to describe people, SNS, resources, social ties, with which we could achieve the interoperability and federation of social net-working system. Based on FOAF framework, we propose SSRA extension as our semantic model, and then build social networking federation system based on it. By this way, we build a semantic and uniform social networking platform, which will change the mode of social networking application, and bring large imagination space for future social network-ing application.