The use of science to understand its own structure is becoming popular, but understanding
the organization of knowledge areas is still limited because some patterns are only
discoverable with proper computational treatment of large-scale datasets. In this paper, we
introduce a framework to combine network-based methodologies and text analytics to
construct the taxonomy of science fields. The methodology is illustrated with application to
two topics: complex networks (CN) and photonic crystals (PC). We built citation networks …