A social network is a useful model for identifying hidden structures and meaningful knowledge among social atoms, which have complicated interactions. In recent years, most studies have focused on the real data of the social space such as emails, tweets, and human communities. In this paper, we construct a social network from literary fiction by mapping characters to vertices and their relationship strengths to edges. The main contribution of this paper is that our model can be exploited to reveal the deep structures of fiction novels by using graph theoretic concepts, without the involvement of any manual work. Experimental evaluation showed that our model successfully classified fictional characters in terms of their importance to the plot of a novel.