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.

中文翻译：

---

科学科学中的预测方法和应用：调查

科学科学已经成为一个热门话题，引起了研究界的极大关注。数据分析技术的发展和现成的学术数据使探索数据驱动的预测成为可能，这在发现科学影响趋势方面起着举足轻重的作用。在本文中，我们分析了科学科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，我们介绍背景并回顾科学科学的现状。其次，我们回顾了基于论文引用计数的数据驱动预测，并调查了该领域的研究问题。然后，我们讨论了预测学者影响的方法，并分析了在协作网络中促进学术协作的不同方法。