Topological Studies Of Science Studies Citation Network

Citation network is known as one of the most important path of knowledge production and diffusion. With the rapid increase of knowledge, a large scale citation network is formed. In scientometrics field, however, there are few scholar studies about it, especially about knowledge production and diffusion in citation network. The present paper combines complex network theory and social network analysis to study Science Studies citation network from macro, mecro, and micro level and discusses the influence of the network structure to the knowledge diffusion.Authoritative control is used to correct some mistakes in the data which was downloaded from SCI in order to make the study effectly. We discover that the Science Studies citation network is a scale-free, small-world, and high clustering network. The structure of the citation is proper to the knowledge fast diffusion, but the path needs to be optimized deeply.According to the distribution of the components, we discuss the whole status of knowledge flowing. On the basis of the biggest component, we apply "centrality" approach in social network analysis to evaluate the literature tentatively that means not only the frequency of being cited is important, who cite and whether occupy an important position in the knowledge flowing network should also be considered.k-core method in social network analysis is also being employed. Based on k-core analysis, we discover the citation analysis is the core in the Science Studies citation network and is the most important sub-study field. The following is cooperation studies, evaluation indicators, and correlation study. Correlation study is closed to the citation analysis which shows citation approches are very important in evaluation. There are three clusters in high in-degree network clearly. The differences of study contents are the main reason of cluster structure's formation.