Lee Seungpeel, Kim Jisu, Choi Eun Been, Shin Sojung, Kim Dogun, Yu HyeRim, Kim Seoyun, Na Wongi S, Park Eunil
Department of Applied Artificial Intelligence, Sungkyunkwan University, Seoul 03063, Korea.
Sahoipyoungnon Publishing Co., Inc., Seoul 03993, Korea.
Math Biosci Eng. 2022 Sep 21;19(12):13911-13927. doi: 10.3934/mbe.2022648.
Since information and communication technology (ICT) has become one of the leading and essential fields for allowing developing countries to have the major growth engines, the majority of the countries have promoted collaboration in every ICT-related topics. In this study, we performed the trend and collaboration network analysis (CNA) in Korea for 2010-2019 among researchers who are related to human-computer interaction, one of the hottest research areas in ICT. Publication data were collected from SciVal, and the collaboration network was determined using degree, closeness, betweenness centralities, and PageRank. Hence, key researchers were identified based on their centrality metrics. The dataset contained 7,155 publications, thus reflecting the contributions of a total of 243 authors. The results of our data analysis demonstrated that key researchers can be identified via CNA; this aspect was not evident from the results of the most productive researchers. Additionally, on the basis of the results, the implications and limitations of this study were analyzed.
由于信息通信技术（ICT）已成为使发展中国家拥有主要增长引擎的主导性和基础性领域之一，大多数国家都在促进在每一个与ICT相关主题上的合作。在本研究中，我们对2010 - 2019年韩国在人机交互（ICT领域最热门的研究领域之一）相关研究人员中进行了趋势和合作网络分析（CNA）。从SciVal收集了出版物数据，并使用度中心性、接近中心性、中介中心性和PageRank确定了合作网络。因此，基于他们的中心性指标确定了关键研究人员。该数据集包含7155篇出版物，从而反映了总共243位作者的贡献。我们的数据分析结果表明，可以通过CNA识别关键研究人员；这一点在产出最多的研究人员的结果中并不明显。此外，基于这些结果，分析了本研究的意义和局限性。
