Abstract:

Theory plays a key role in disciplinary development and scientific research. The application and development of theory in research represent the academic maturity of the field, Theoretical poverty and discipline independence has been a problem of information science all the time. In order to investigate the application and development of theory in information science research in China, this paper conducted statistics and analysis on the theoretical research patterns and academic influence of academic journal articles. Instead of keyword search and sampling statistics which were used by other similar research, this paper analyzed all the 52 kinds of LIS journal papers from 2008 to 2017. By using rules and artificial selection, 40260 information science papers were identified and chosen from the 107740 academic papers. Then a theoretical recognition model was developed by using Natural Language Processing and deep learning method with automatic identification and manual auditing. On the basis of multidimensional statistics including time, journal source, researching field and patterns of these papers, the respective influences of theoretical research on information science, library and information science, social disciplines and the general subject study were compared and analyzed. Finally several important conclusions have been drawn. This study will have great significance for comprehensively understanding the theoretical research structure of information science, illustrating the shortage and demand of theoretical research, and will also help guide the construction of the theoretical system and the development of the discipline.

Keywords: Information science, Theoretical research patterns, Theoretical research fields, Academic influence, Theoretical terms recognition model, Deep learning