This paper elaborates how to identify and evaluate causal factors to improve
scientific impact. Currently, analyzing scientific impact can be beneficial to
various academic activities including funding application, mentor
recommendation, and discovering potential cooperators etc. It is universally
acknowledged that high-impact scholars often have more opportunities to receive
awards as an encouragement for their hard working. Therefore, scholars spend
great efforts in making scientific achievements and improving scientific impact
during their academic life. However, what are the determinate factors that
control scholars' academic success? The answer to this question can help
scholars conduct their research more efficiently. Under this consideration, our
paper presents and analyzes the causal factors that are crucial for scholars'
academic success. We first propose five major factors including
article-centered factors, author-centered factors, venue-centered factors,
institution-centered factors, and temporal factors. Then, we apply recent
advanced machine learning algorithms and jackknife method to assess the
importance of each causal factor. Our empirical results show that
author-centered and article-centered factors have the highest relevancy to
scholars' future success in the computer science area. Additionally, we
discover an interesting phenomenon that the h-index of scholars within the same
institution or university are actually very close to each other.

本论文探讨了科研影响力的关键控制因素并借助机器学习和 Jackknife 方法进行实证分析，结果发现文章中心因素和作者中心因素对计算机科学领域的学者未来的学术成功最具关联性。