论文标题

探索学术职业成功的混杂因素:一项具有深刻预测建模的实证研究

Exploring the Confounding Factors of Academic Career Success: An Empirical Study with Deep Predictive Modeling

论文作者

Du, Chenguang, Wang, Deqing, Zhuang, Fuzhen, Zhu, Hengshu

论文摘要

了解学术职业成功的决定因素对学者及其雇用组织至关重要。尽管已经朝这个方向进行了大量的研究工作,但由于巨大的混杂因素,仍缺乏对学者职业进行建模的定量方法。为此,在本文中,我们建议通过经验和预测性建模的观点探索学术职业成功的决定因素,重点是两个典型的学术荣誉,即IEEE研究员和ACM研究员。我们定量分析不同因素的重要性,并获得一些有见地的发现。具体而言,我们分析了共同作者网络,并发现潜在的学者在成长的早期和更紧密地与有影响力的学者紧密合作。然后,我们比较男性和女性研究员的学习成绩。比较后,我们发现要当选,女性需要比男性更多的努力。此外,我们还发现,成为同胞无法提高引用和生产力增长。我们希望这些衍生的因素和发现可以帮助学者提高其竞争力并在学术职业中发展良好。

Understanding determinants of success in academic careers is critically important to both scholars and their employing organizations. While considerable research efforts have been made in this direction, there is still a lack of a quantitative approach to modeling the academic careers of scholars due to the massive confounding factors. To this end, in this paper, we propose to explore the determinants of academic career success through an empirical and predictive modeling perspective, with a focus on two typical academic honors, i.e., IEEE Fellow and ACM Fellow. We analyze the importance of different factors quantitatively, and obtain some insightful findings. Specifically, we analyze the co-author network and find that potential scholars work closely with influential scholars early on and more closely as they grow. Then we compare the academic performance of male and female Fellows. After comparison, we find that to be elected, females need to put in more effort than males. In addition, we also find that being a Fellow could not bring the improvements of citations and productivity growth. We hope these derived factors and findings can help scholars to improve their competitiveness and develop well in their academic careers.

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