Research on the development trend of cross-disciplinary subjects in universities with electronic information characteristics based on the analysis of citation data--The example of " Chinese electronic information universities"
Year: 2024
Type: preprint
Abstract: With the promotion of the construction of "double first-class" and the deepening of cross-disciplinary research, as well as the needs of the development of the electronic information industry, the electronic information characteristics of universities represented by Beijing University of Posts and Telecommunications (BUPT), University of Electronic Science and Technology (UEST) and Xi'an University of Electronic Science and Technology (XUEST) have actively developed cross-disciplines to improve their strengths in running schools. This paper takes Web of science™ core collection database and ESI database as the data source, collects the highly cited paper literature data of these three universities with electronic information characteristics, adopts visual analysis technology, intelligent intelligence analysis technology and data mining technology to analyze the current situation of the development of their cross-disciplines, analyze the cross-discipline development situation of the universities with electronic information characteristics, and puts forward the suggestions to promote the high-quality development of cross-disciplines in the universities with electronic information characteristics. We will analyze the current situation of cross-disciplinary development, analyze the development situation of cross-disciplinary development in universities with electronic information characteristics, and put forward suggestions to promote the high-quality development of cross-disciplines in universities with electronic information characteristics.
Source: Research Square
Authors: QIAN WANG, WEI JIA, YUQING LI, ZHENYUAN SHI, YIYI XING
Institution: Beijing University of Posts and Telecommunications
Language: English
Subfield: Statistics, Probability and Uncertainty
Field: Decision Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W4400996690