图灵指数——学术大数据下的跨领域跨年代学者影响力评估

doi:10.11959/j.issn.2096-0271.2019039

Abstract

Abstract:

Gauging the impact of scholars,despite numerous quantitative indicators proposed,remains hard thanks to nowadays gigantic and inflating academic networks accompanied by huge disparity among domains and generations.Data collected from 14 223 183 scholars,126 438 664 papers,533 556 856 references across 310 domains with a time spanning of year 1865 to 2016,suggest universe power-law distributed yearly increased citations of scholars across domains and generations.Turing index then eliminates the inflation via normalizing different scaling parameters in those power law distributions to assess the absolute domain impact of each scholar.Comparison of Turing index among renowned scholars like Nobel,Fields Medal and Turing laureates confirms their equal significance to their dedicated domains despite the vast domain discrepancies in generations and citations.Turing index provides a new way of thinking for cross-domain and cross-generation impact evaluation,and can provide reference for scholars’ impact assessment and national science foundations worldwide.

Key words: impact evaluation, Turing index, big data mining, academic network

CLC Number:

TN929.5

Yuhang YAO, Junjie OU, Yang LI, Luoyi FU, Xinbing WANG, Guihai CHEN. Turing index:cross-domain and cross-generation metric of unraveling scholars’ impact in academic big data[J]. Big Data Research, 2019, 5(5): 25-37.

Figures/Tables 11

References 42

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主要领域	论文数/篇	引用量/次	学者数/位	子领域数/个	时间
政治学	229 474	130 713	174 908	250	1928—2016年
药学	6 593836	4 798 767	6 699 626	1 675	1875—2016年
哲学	1367 394	935 214	1 321 093	1 665	1874—2016年
化学	7 717 267	5 510 693	6 262 877	3 522	1865—2016年
经济学	3 928 782	2 801 510	3 313 730	2 349	1906—2016年
历史学	620 355	390 641	727 469	656	1890—2016年
数学	7 909 950	5 885 640	5 487 308	8 025	1889—2016年
生物学	7 751 483	5 619 200	7 038 316	4 174	1888—2016年
计算机科学	7 512 849	5 718 499	5 474 060	5 181	1889—2016年
材料科学	2 553 860	1 854 914	2 325 120	945	1902—2016年
社会学	3 107 882	2 130 742	2 755 201	2 048	1897—2016年
地质学	2 624 463	1 873 559	2 570 621	2 120	1895—2016年
心理学	4 354 577	3 145 985	4 278 842	2 430	1897—2016年
环境科学	441 410	289 355	585 570	178	1901—2016年
物理学	9 471 698	6 707 746	6 142 982	6 620	1865—2016年
工程学	5 819 259	4 323 780	4 374 996	2 689	1889—2016年
艺术学	456 271	320 508	548 785	422	1910—2016年
地理学	571 233	423 779	665 790	502	1912—2016年
商学	1 086 437	767 941	1 151 164	536	1894—2016年

姓名	获奖名称	年份	贡献	引用量/次	图灵指数
Arieh Warshel	诺贝尔化学奖	2013年	复杂化学系统	3 222	2 254
Barbara Mcclintock	诺贝尔生理学或医学奖	1983年	可移动遗传因子	3 809	2 245
Bruce Beutler	诺贝尔生理学或医学奖	2011年	先天免疫活化	15 650	4 558
Edmund M Clarke	图灵奖	2007年	模型检查	13 882	6 078
Eric Betzig	诺贝尔化学奖	2014年	荧光显微镜	6 422	4 509
Jean Tirole	诺贝尔经济学奖	2013年	市场权力及规管	3 031	5 650
Johann Deisenhofer	诺贝尔化学奖	1988年	光合作用中心	5 696	3 662
John E Hopcroft	图灵奖	1986年	算法设计	8 449	6 020
Oliver E Williamson	诺贝尔经济学奖	2009年	经济治理	5 131	5 237
Paul Nurse	诺贝尔生理学或医学奖	2001年	细胞周期调节器	11 048	2 613
Pierrelouis Lions	菲尔兹奖	1994年	偏微分方程	3 908	2 747
Ralph M Steinman	诺贝尔生理学或医学奖	2011年	树突细胞	18 683	5 820
Roald Hoffmann	诺贝尔化学奖	1981年	化学反应过程	1 737	2 261
Shuji Nakamura	诺贝尔物理学奖	2014年	蓝色发光二极管	4 412	2 832
Susumu Tonegawa	诺贝尔生理学或医学奖	1987年	抗体的多样性	17 419	5 150
Sydney Brenner	诺贝尔生理学或医学奖	2002年	基因调控	6 896	2 125
Terence Tao	菲尔兹奖	2006年	偏微分方程	9 706	3 750

Turing index:cross-domain and cross-generation metric of unraveling scholars’ impact in academic big data

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References 42

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