  A typical social research topic is to figure out the influential people's
relationship and its weights. It is very tedious for social scientists to solve
those problems by studying massive literature. Digital humanities bring a new
way to a social subject. In this paper, we propose a framework for social
scientists to find out ancient figures' power and their camp. The core of our
framework consists of signed graph model and novel group partition algorithm.
We validate and verify our solution by China Biographical Database Project
(CBDB) dataset. The analytic results on a case study demonstrate the
effectiveness of our framework, which gets information that consists with the
literature's facts and social scientists' viewpoints.
