Scientific impact plays a central role in the evaluation of the output of
scholars, departments, and institutions. A widely used measure of scientific
impact is citations, with a growing body of literature focused on predicting
the number of citations obtained by any given publication. The effectiveness of
such predictions, however, is fundamentally limited by the power-law
distribution of citations, whereby publications with few citations are
extremely common and publications with many citations are relatively rare.
Given this limitation, in this work we instead address a related question asked
by many academic researchers in the course of writing a paper, namely: "Will
this paper increase my h-index?" Using a real academic dataset with over 1.7
million authors, 2 million papers, and 8 million citation relationships from
the premier online academic service ArnetMiner, we formalize a novel scientific
impact prediction problem to examine several factors that can drive a paper to
increase the primary author's h-index. We find that the researcher's authority
on the publication topic and the venue in which the paper is published are
crucial factors to the increase of the primary author's h-index, while the
topic popularity and the co-authors' h-indices are of surprisingly little
relevance. By leveraging relevant factors, we find a greater than 87.5%
potential predictability for whether a paper will contribute to an author's
h-index within five years. As a further experiment, we generate a
self-prediction for this paper, estimating that there is a 76% probability that
it will contribute to the h-index of the co-author with the highest current
h-index in five years. We conclude that our findings on the quantification of
scientific impact can help researchers to expand their influence and more
effectively leverage their position of "standing on the shoulders of giants."

该论文研究了科学影响力的衡量指标，使用真实学术数据集分析研究者的学术影响力指标 h-index 的提高因素，指出研究者在该主题领域的权威性以及论文发表的期刊是提高 h-index 的关键因素。