Trend Analysis of Innovative Talents Based on the Data Visualization Using the Chinese Social Science Data
- DOI
- 10.2991/978-94-6463-034-3_110How to use a DOI?
- Keywords
- Innovation talents; CSSCI literature; KH coder; High frequency vocabulary; Co-occurrence network diagram
- Abstract
In this study, we analyzed the literature data of innovative talents recorded in Chinese Social Sciences Citation Index using the KH Coder software and examined the academic development, research contents, and research trends of the innovative talents research in China. By analyzing the changes in the frequency of high-frequency words and the co-occurrence network diagram reflecting the visualization of relationships, we found that the research on innovative talents in China has always been focused on how to cultivate innovative talents, but the attention to “creativity” and “thinking” has decreased. At the same time, the research on innovation and entrepreneurship education, which focuses on the cultivation of innovative talents, has become a new field and trend in the research on the innovative talents in China.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Xiaoling Yu AU - Takaya Yuizono PY - 2022 DA - 2022/12/23 TI - Trend Analysis of Innovative Talents Based on the Data Visualization Using the Chinese Social Science Data BT - Proceedings of the 2022 3rd International Conference on Big Data and Informatization Education (ICBDIE 2022) PB - Atlantis Press SP - 1079 EP - 1086 SN - 2589-4900 UR - https://doi.org/10.2991/978-94-6463-034-3_110 DO - 10.2991/978-94-6463-034-3_110 ID - Yu2022 ER -