A generative model for scientific concept hierarchies.

ABSTRACT: In many scientific disciplines, each new 'product' of research (method, finding, artifact, etc.) is often built upon previous findings-leading to extension and branching of scientific concepts over time. We aim to understand the evolution of scientific concepts by placing them in phylogenetic hierarchies where scientific keyphrases from a large, longitudinal academic corpora are used as a proxy of scientific concepts. These hierarchies exhibit various important properties, including power-law degree distribution, power-law component size distribution, existence of a giant component and less probability of extending an older concept. We present a generative model based on preferential attachment to simulate the graphical and temporal properties of these hierarchies which helps us understand

SUBMITTER: Datta S 

PROVIDER: S-EPMC5825074 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature