Frequency and Link Analysis of Online Novels Toward Social Contents Ranking

User generated contents service is a social service because users not only enjoy contents but also provide feedback on content by commenting, tagging and book marking. The authors are interested in social service ranking and categorization methods for online novels. Many readers comment and bookmark there favorite novels in online novel services. Comments and book marking are facilitated by readers, and it is possible to use the data as a resource for social ranking and recommendation. In this paper, we focused on an online novel service, and analyzed the frequency of keywords, number of authors, and links from readers to novels. Although the bipartite graph between readers and novels fulfills growth and preferential attachment conditions of scale-free network, distribution of links does not follow power law. The basic idea of social ranking using extracted book marked novels and favorite authors is also explored.