A bibliometrics-based research framework for exploring policy evolution: A case study of China's information technology policies

Abstract

Qualitative methods for analyzing policy evolution are often unequipped to process high volumes of policy texts that involve many domains and long timespans. This makes it difficult to take full advantage of the semantic information contained in policy literature. It is also difficult to use traditional qualitative methods to systematically analyze the characteristics of a complex policy mix network, such as the locations, evolution, and relationships between policy actors/targets. In order to address these issues, we propose a bibliometrics-based research framework for exploring policy evolution. We first collect all relevant policy documents from a target domain. We then construct networks of policymaker based on co-occurrence relationships in policy promulgation, in order to determine core policymakers, as well as changes in their status in the networks over time. Lastly, we use semantic analysis to identify policy targets and construct policy target keyword co-occurrence networks for discrete time periods. The evolution of a specific policy domain can then be examined based on changes in network centrality. Information technology policies in China were used as a case study to demonstrate the reliability of our method. The results reflect the practical value of using this method for the quantitative analysis of policy documents.