论文标题
通过关键字共呈现网络揭示韩国物理协会的作用
Revealing role of Korean Physics Society with keyword co-occurrence network
论文作者
论文摘要
科学与社会不可避免地互相互动并共同发展。研究科学趋势有助于认识到领先的主题对研究的重要性,并制定更好的政策以有效地分配资金。诸如韩国物理学会(KP)等学术社会在科学史上也起着重要作用。弄清楚这些学术社会的作用激发了我们与社会有关的研究,因为社会要注意改善我们的社会。尽管几项研究试图捕捉科学的趋势利用纸张或专利等科学文档,但这些研究仅将其研究范围限制在学术界,忽略了与社会的互动。在这里,我们尝试使用韩国物理学会(KPS)出版的名为“物理与高科技”的公共杂志“物理与高科技”的公共杂志来了解科学的趋势。我们为每个时间段构建关键字共发生网络,并应用社区检测以捕获关键字结构并跟踪结构的演变。在网络中,随着时间的流逝,与研究相关的群集始终是占主导地位的,与研究相关的群集的子群体分为各种物理领域,这意味着物理学科的专业化。另外,我们发现教育和政策集群始终如一地出现,揭示了KPS对科学和社会的贡献。此外,我们将Pagerank算法应用于选定的关键字(“半导体”,“女人”,“逃避” ...),以研究网络中关键字的重要性的时间变化。例如,随着时间的流逝,关键字“女人”的重要性增加了,这表明学术界还注意反映了近年来社会运动的性别问题。
Science and society inevitably interact with each other and evolve together. Studying the trend of science helps recognize leading topics significant for research and establish better policies to allocate funds efficiently. Scholarly societies such as the Korean Physics Society (KPS) also play an important role in the history of science. Figuring out the role of these scholarly societies motivate our research related with our society since societies pay attention to improve our society. Although several studies try to capture the trend of science leveraging scientific documents such as paper or patents, but these studies limited their research scope only to the academic world, neglecting the interaction with society. Here we try to understand the trend of science along with society using a public magazine named "Physics and High Technology," published by the Korean Physics Society (KPS). We build keyword co-occurrence networks for each time period and applied community detection to capture the keyword structure and tracked the structure's evolution. In the networks, a research-related cluster is consistently dominant over time, and sub-clusters of the research-related cluster divide into various fields of physics, implying specialization of the physics discipline. Also, we found that education and policy clusters appear consistently, revealing the KPS's contribution to science and society. Furthermore, we applied PageRank algorithm to selected keywords ('semiconductor', 'woman', 'evading'...) to investigate the temporal change of the importance of keywords in the network. For example, the importance of the keyword 'woman' increases as time goes by, indicating that academia also pays attention to gender issues reflecting the social movement in recent years.