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Turing Award elites revisited: patterns of productivity, collaboration, authorship and impact

Digital Libraries · Submitted 22 Jun 2021

abstract compiled · 2026-09-23 · no language-model review

The authors' main claim In this article, we extract and analyze the data of 72 Turing Award laureates from the complete bibliographic data, fill the gap in the lack of Turing Award analysis, and discover the development characteristics of computer science as an independent discipline.

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arXiv ID2106.11534 (version 1)
Pith IDQDVARTWR, Pith's permanent record of this paper and its review
CitationJie Tang, Sha Yuan, Wendy Hall, Yinyu Jin, Zhou Shao. "Turing Award elites revisited: patterns of productivity, collaboration, authorship and impact." arXiv:2106.11534 (2021). https://pith.science/paper/QDVARTWR
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The compiled record

The paper's own sentences, arranged. Each label is drawn from a closed vocabulary; the number beside it is the probability the classifier gave that label. Numbers in the tables are the authors', checked by code. No sentence in this record was written by a model.

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Compiled by classifier-1.13.0 via TypeSafe API, question bank abstract-p1-20260923, 2026-09-23: 1 request, 8,319 input tokens.

What the abstract itself states, as probabilities: claims first 0.29 · states limitation 0.13 · human participants 0.12 · controlled comparison 0.05 · randomized assignment 0.01 · states quantitative result 0.98 · compares with prior results 0.16 · mentions code or data availability 0.02.

The abstract, sentence by sentence

arXiv listing abstract v1. Results and the main claim are underlined; .

The Turing Award is recognized as the most influential and prestigious award in the field of computer science(CS). With the rise of the science of science (SciSci), a large amount of bibliographic data has been analyzed in an attempt to understand the hidden mechanism of scientific evolution. These include the analysis of the Nobel Prize, including physics, chemistry, medicine, etc. In this article, we extract and analyze the data of 72 Turing Award laureates from the complete bibliographic data, fill the gap in the lack of Turing Award analysis, and discover the development characteristics of computer science as an independent discipline. First, we show most Turing Award laureates have long-term and high-quality educational backgrounds, and more than 61% of them have a degree in mathematics, which indicates that mathematics has played a significant role in the development of computer science. Secondly, the data shows that not all scholars have high productivity and high h-index; that is, the number of publications and h-index is not the leading indicator for evaluating the Turing Award. Third, the average age of awardees has increased from 40 to around 70 in recent years. This may be because new breakthroughs take longer, and some new technologies need time to prove their influence. Besides, we have also found that in the past ten years, international collaboration has experienced explosive growth, showing a new paradigm in the form of collaboration. It is also worth noting that in recent years, the emergence of female winners has also been eye-catching. Finally, by analyzing the personal publication records, we find that many people are more likely to publish high-impact articles during their high-yield periods.

background contribution method result interpretation main claim

What the classifier reports for each sentence. The number is the probability it gave the label.
#sentencerolethe authors' own workstates the main conclusionstrength
s0 The Turing Award is recognized as the most influential and prestigious award in the field of computer science(CS). background 1.00 0.04 0.02 asserted 1.00
s1 With the rise of the science of science (SciSci), a large amount of bibliographic data has been analyzed in an attempt to understand the hidden mechanism of scientific evolution. background 1.00 0.05 0.02 asserted 0.99
s2 These include the analysis of the Nobel Prize, including physics, chemistry, medicine, etc. background 1.00 0.09 0.02 asserted 0.92
s3 In this article, we extract and analyze the data of 72 Turing Award laureates from the complete bibliographic data, fill the gap in the lack of Turing Award analysis, and discover the development characteristics of computer science as an independent discipline. contribution 0.98 0.96 0.14 asserted 1.00
s4 First, we show most Turing Award laureates have long-term and high-quality educational backgrounds, and more than 61% of them have a degree in mathematics, which indicates that mathematics has played a significant role in the development of computer science. result 0.98 0.91 0.14 asserted 0.89
s5 Secondly, the data shows that not all scholars have high productivity and high h-index; that is, the number of publications and h-index is not the leading indicator for evaluating the Turing Award. result 0.93 0.92 0.24 asserted 1.00
s6 Third, the average age of awardees has increased from 40 to around 70 in recent years. result 1.00 0.90 0.08 asserted 1.00
s7 This may be because new breakthroughs take longer, and some new technologies need time to prove their influence. interpretation 1.00 0.20 0.04 hedged possibility 1.00
s8 Besides, we have also found that in the past ten years, international collaboration has experienced explosive growth, showing a new paradigm in the form of collaboration. result 1.00 0.93 0.08 asserted 1.00
s9 It is also worth noting that in recent years, the emergence of female winners has also been eye-catching. result 1.00 0.75 0.04 asserted 1.00
s10 Finally, by analyzing the personal publication records, we find that many people are more likely to publish high-impact articles during their high-yield periods. result 1.00 0.96 0.10 asserted 0.69

What kind of paper the classifier reports this is: empirical study 1.00 · evidence from analysis of existing data 1.00.

What was examined, and what was not

sources read
  • arXiv listing abstract v1
not examined
  • full text
  • figures and tables
  • references and citing sentences
  • relations to other papers
levels run
  • P abstract
not run
  • S sections
  • T body sentences
  • C citations
  • R cross-paper relations

Every quoted sentence on this record is the authors'. Every label is from Pith's closed vocabulary, with the probability shown beside it. Every number in the measurements table is the authors', checked by code. Record as JSON

The paper
Original abstract

The Turing Award is recognized as the most influential and prestigious award in the field of computer science(CS). With the rise of the science of science (SciSci), a large amount of bibliographic data has been analyzed in an attempt to understand the hidden mechanism of scientific evolution. These include the analysis of the Nobel Prize, including physics, chemistry, medicine, etc. In this article, we extract and analyze the data of 72 Turing Award laureates from the complete bibliographic data, fill the gap in the lack of Turing Award analysis, and discover the development characteristics of computer science as an independent discipline. First, we show most Turing Award laureates have long-term and high-quality educational backgrounds, and more than 61% of them have a degree in mathematics, which indicates that mathematics has played a significant role in the development of computer science. Secondly, the data shows that not all scholars have high productivity and high h-index; that is, the number of publications and h-index is not the leading indicator for evaluating the Turing Award. Third, the average age of awardees has increased from 40 to around 70 in recent years. This may be because new breakthroughs take longer, and some new technologies need time to prove their influence. Besides, we have also found that in the past ten years, international collaboration has experienced explosive growth, showing a new paradigm in the form of collaboration. It is also worth noting that in recent years, the emergence of female winners has also been eye-catching. Finally, by analyzing the personal publication records, we find that many people are more likely to publish high-impact articles during their high-yield periods.

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