Dynamic transition of scientific teams based on time slicing

Based on dynamic research perspectives of time slicing, this paper shows an endeavor on mining dynamic features of the scientific teams. Traditionally the static method of network structure analysis can successfully be used to analyze the distribution of network resource structure. But it cannot be used to explore the dynamic features of research groups, because of its lacks on the influence of some variables in research activities. These variables include researchers, research hotspots and research funds, etc. which are all in varying state due to the changing world. This paper proposes a new approach to analyze the dynamic characteristics of scientific teams, by using time slicing incorporated with traditional static method. KP(core members Keep-Rate) is used as an index of the dynamic transitions of scientific teams in two sequential time slices, and an algorithm is proposed to identify the successor team(s).