预测方法及其在科学学中的应用
Prediction Methods and Applications in the Science of Science: A Survey
摘要：
科学学已成为研究界关注的热门话题。数据分析技术的发展和现成的学术数据使数据驱动预测的探索成为可能，这在发现科学影响的趋势方面起着关键作用。本文分析了科学学中数据驱动预测的方法和应用，并讨论了它们的意义。首先，我们介绍了科学学的研究背景，回顾了科学学的研究现状。其次，我们回顾了基于论文引用计数的数据驱动预测，并调查了这一领域的研究问题。然后，我们讨论了预测学者影响的方法，并分析了不同的方法来促进学术合作的合作网络。本文还讨论了开放的问题和现有的挑战，并提出了潜在的研究方向。
英文摘要：
Science of science has become a popular topic that attracts great attentions from the research community. The development of data analytics technologies and the readily available scholarly data enable the exploration of data-driven prediction, which plays a pivotal role in finding the trend of scientific impact. In this paper, we analyse methods and applications in data-driven prediction in the science of science, and discuss their significance. First, we introduce the background and review the current state of the science of science. Second, we review data-driven prediction based on paper citation count, and investigate research issues in this area. Then, we discuss methods to predict scholar impact, and we analyse different approaches to promote the scholarly collaboration in the collaboration network. This paper also discusses open issues and existing challenges, and suggests potential research directions.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
