Computer science has grown rapidly since its inception in the 1950s and the pioneers in the field are celebrated annually by the A.M. Turing Award. In this paper, we attempt to shed light on the path to influential computer scientists by examining the characteristics of the 72 Turing Award laureates. To achieve this goal, we build a comprehensive dataset of the Turing Award laureates and analyze their characteristics, including their personal information, family background, academic background, and industry experience. The FP-Growth algorithm is used for frequent feature mining. Logistic regression plot, pie chart, word cloud and map are generated accordingly for each of the interesting features to uncover insights regarding personal factors that drive influential work in the field of computer science. In particular, we show that the Turing Award laureates are most commonly white, male, married, United States citizen, and received a PhD degree. Our results also show that the age at which the laureate won the award increases over the years; most of the Turing Award laureates did not major in computer science; birth order is strongly related to the winners' success; and the number of citations is not as important as one would expect.
翻译:自1950年代开始以来,计算机科学迅速发展,该领域的先驱每年由A.M.图灵奖庆祝。在本文中,我们试图通过审查图灵奖72名获奖者的特点,阐明通往有影响力的计算机科学家的道路。为实现这一目标,我们建立了图灵奖得主的综合数据集,并分析了其特征,包括其个人信息、家庭背景、学术背景和行业经验。FP-Growth算法用于频繁的地貌采矿。后勤回归图、派图、字云和地图都相应地生成了每一个有趣的特征,以揭示在计算机科学领域推动有影响力工作的个人因素的洞察力。特别是,我们显示图灵奖得主通常是白人、男性、已婚、美国公民,并获得博士学位。我们的结果还显示,多年来获奖者获得奖的年龄有所上升;图灵奖得主大多在计算机科学方面并不重要;出生顺序与获奖者的成功密切相关;引文数量并不如人们所期望的那样重要。