跨维度特征融合视角下的科技论文新颖性测量方法研究

doi:10.3772/j.issn.1000-0135.2025.03.007

情报学报

2025, Vol. 44

Issue (3): 339-352 DOI: 10.3772/j.issn.1000-0135.2025.03.007

情报技术与应用

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跨维度特征融合视角下的科技论文新颖性测量方法研究

马铭¹, 郑哲浚², 毛进^3,4, 白云³, 李纲⁴

1.南京大学数据管理创新研究中心，苏州 215163
2.南京大学信息管理学院，南京 210023
3.武汉大学信息管理学院，武汉 430072
4.武汉大学信息资源研究中心，武汉 430072

Measuring the Novelty of Scientific Papers Using Cross-dimensional Feature Integration

Ma Ming¹, Zheng Zhejun², Mao Jin^3,4, Bai Yun³, Li Gang⁴

1.Research Institute for Data Management & Innovation, Nanjing University, Suzhou 215163
2.School of Information Management, Nanjing University, Nanjing 210023
3.School of Information Management, Wuhan University, Wuhan 430072
4.Center for Studies of Information Resources, Wuhan University, Wuhan 430072

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摘要准确评估科技论文的内在新颖性，对追踪学术前沿和实现高质量科研创新评价具有重要意义。本文基于科技论文的知识内容和学术交流结构，创新性地提出一种跨维度特征融合视角下的科技论文新颖性测量新方法，以全面、客观地评估科技论文的新颖性。首先，基于“问题-方法”组合，构建科技论文的结构化知识表示模型，并利用领域预训练语言模型为组合赋权；其次，考虑知识内容和学术交流结构，围绕原创性、复杂性和研究热度等事前特征，构建科技论文新颖性的跨维度综合测量指标；最后，通过对生物医学领域数据集的实证分析以及新颖性论文的事后影响力检验，证明了本文方法的有效性。实证分析结果表明，本文方法不受时间和环境因素干扰，能够在长时间跨度内保持方法效力并有效挖掘领域论文的新颖性模式。此外，与单一维度方法的对比证明了新方法能够更好地综合捕捉多维复合特征评估新颖性论文，避免了测量维度的单一化与片面化。本文为科技论文新颖性测度提供了新的视角和方法，同时可作为科研工作者识别和推广创新性研究的有效工具。

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	马铭
	郑哲浚
	毛进
	白云
	李纲

关键词 ：新颖性测量, 跨维度特征融合, “问题-方法”组合, 事前特征, 事后影响力

收稿日期: 2024-05-28

基金资助:国家自然科学基金面上项目“基于‘问题-方法’关联识别的科学知识创新探测与协同演化分析”（72174154）；江苏省研究生科研与实践创新计划项目“双链融合视角下的战略新兴产业弱信号识别研究”（KYCX24_0315）。

作者简介: 马铭，男，1995年生，博士研究生，主要研究方向为科技预测、科学评价；郑哲浚，男，2000年生，博士研究生，主要研究方向为科技预测与数据挖掘；毛进，通信作者，男，1988年生，博士，副教授，博士生导师，主要研究方向为信息组织、大数据分析，E-mail：danveno@163.com；白云，女，1997年生，博士研究生，主要研究方向为科学社会学；李纲，男，1966年生，博士，教授，博士生导师，主要研究方向为信息资源管理、竞争情报；

引用本文:

马铭, 郑哲浚, 毛进, 白云, 李纲. 跨维度特征融合视角下的科技论文新颖性测量方法研究[J]. 情报学报, 2025, 44(3): 339-352.
Ma Ming, Zheng Zhejun, Mao Jin, Bai Yun, Li Gang. Measuring the Novelty of Scientific Papers Using Cross-dimensional Feature Integration. 情报学报, 2025, 44(3): 339-352.

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https://qbxb.istic.ac.cn/CN/10.3772/j.issn.1000-0135.2025.03.007 或 https://qbxb.istic.ac.cn/CN/Y2025/V44/I3/339

1 Harvey S, Berry J W. Toward a meta-theory of creativity forms: how novelty and usefulness shape creativity[J]. Academy of Management Review, 2023, 48(3): 504-529.
2 George J M. Creativity in organizations[J]. The Academy of Management Annals, 2007, 1(1): 439-477.
3 George J M, Zhou J. When openness to experience and conscientiousness are related to creative behavior: an interactional approach[J]. Journal of Applied Psychology, 2001, 86(3): 513-524.
4 杨锋, 梁棵, 苟清龙, 等. 同行评议制度缺陷的根源及完善机制[J]. 科学学研究, 2008, 26(3): 569-572.
5 杨京, 王芳, 白如江. 一种基于研究主题对比的单篇学术论文创新力评价方法[J]. 图书情报工作, 2018, 62(17): 75-83.
6 Luo Z R, Lu W, He J G, et al. Combination of research questions and methods: a new measurement of scientific novelty[J]. Journal of Informetrics, 2022, 16(2): 101282.
7 Uzzi B, Mukherjee S, Stringer M, et al. Atypical combinations and scientific impact[J]. Science, 2013, 342(6157): 468-472.
8 Wang J, Veugelers R, Stephan P. Bias against novelty in science: a cautionary tale for users of bibliometric indicators[J]. Research Policy, 2017, 46(8): 1416-1436.
9 Fleming L. Recombinant uncertainty in technological search[J]. Management Science, 2001, 47(1): 117-132.
10 Min C, Bu Y, Sun J J. Predicting scientific breakthroughs based on knowledge structure variations[J]. Technological Forecasting and Social Change, 2021, 164: 120502.
11 Verhoeven D, Bakker J, Veugelers R. Measuring technological novelty with patent-based indicators[J]. Research Policy, 2016, 45(3): 707-723.
12 《科技查新教程》编写组. 科技查新教程[M]. 北京: 机械工业出版社, 2001.
13 Luzón Marco M J. The construction of novelty in computer science papers[J]. Revista Alicantina de Estudios Ingleses, 2000(13): 123-140.
14 Shibayama S, Yin D Y, Matsumoto K. Measuring novelty in science with word embedding[J]. PLoS One, 2021, 16(7): e0254034.
15 Campbell D T. Blind variation and selective retentions in creative thought as in other knowledge processes[J]. Psychological Review, 1960, 67(6): 380-400.
16 Verhoeven D, Bakker J, Veugelers R. Identifying ex ante characteristics of radical inventions through patent-based indicators[J]. SSRN Electronic Journal, 2013: lirias1830808.
17 Banerjee P M, Cole B M. Globally radical technologies and locally radical technologies: the role of audiences in the construction of innovative impact in biotechnology[J]. IEEE Transactions on Engineering Management, 2011, 58(2): 262-274.
18 Henderson R M, Clark K B. Architectural innovation: the reconfiguration of existing product technologies and the failure of established firms[J]. Administrative Science Quarterly, 1990, 35(1): 9-30.
19 Dosi G. Technological paradigms and technological trajectories[J]. Research Policy, 1982, 11(3): 147-162.
20 Ahuja G, Lampert C M. Entrepreneurship in the large corporation: a longitudinal study of how established firms create breakthrough inventions[J]. Strategic Management Journal, 2001, 22(6/7): 521-543.
21 逯万辉, 苏金燕, 余倩. 学术成果主题新颖性与学术引用的相关关系研究[J]. 情报资料工作, 2018, 39(6): 68-73.
22 Leydesdorff L, Bornmann L, Comins J A, et al. Citations: indicators of quality? the impact fallacy[J]. Frontiers in Research Metrics and Analytics, 2016, 1: 1.
23 Koestler A. The act of creation[M]. London: Macmillan, 1964: 751.
24 Harvey S. Creative synthesis: exploring the process of extraordinary group creativity[J]. Academy of Management Review, 2014, 39(3): 324-343.
25 Hargadon A B, Bechky B A. When collections of creatives become creative collectives: a field study of problem solving at work[J]. Organization Science, 2006, 17(4): 484-500.
26 Azoulay P, Graff Zivin J S, Manso G. Incentives and creativity: evidence from the academic life sciences[J]. The RAND Journal of Economics, 2011, 42(3): 527-554.
27 罗卓然, 陆伟, 蔡乐, 等. 学术文本词汇功能识别——在论文新颖性度量上的应用[J]. 情报学报, 2022, 41(7): 720-732.
28 Kyebambe M N, Cheng G, Huang Y Q, et al. Forecasting emerging technologies: a supervised learning approach through patent analysis[J]. Technological Forecasting and Social Change, 2017, 125: 236-244.
29 Landauer T K, Dumais S T. A solution to Plato’s problem: the latent semantic analysis theory of acquisition, induction, and representation of knowledge[J]. Psychological Review, 1997, 104(2): 211-240.
30 Strübing J. Research as pragmatic problem-solving: the pragmatist roots of empirically-grounded theorizing[M]// The SAGE Handbook of Grounded Theory. Thousand Oaks: SAGE Publications, 2007: 580-602.
31 Mann W C, Thompson S A. Rhetorical Structure Theory: Toward a functional theory of text organization[J]. Text-Interdisciplinary Journal for the Study of Discourse, 1988, 8(3): 243-281.
32 Teufel S. Argumentative zoning: information extraction from scientific text[D]. Edinburgh: The University of Edinburgh, 1999.
33 McShea D W, Wang S C, Brandon R N. A quantitative formulation of biology’s first law[J]. Evolution, 2019, 73(6): 1101-1115.
34 Arts S, Hou J N, Gomez J C. Natural language processing to identify the creation and impact of new technologies in patent text: Code, data, and new measures[J]. Research Policy, 2021, 50(2): 104144.
35 Ericsson K A, Charness N. Cognitive and developmental factors in expert performance[M]// Expertise in Context: Human and Machine. Cambridge: The MIT Press, 1997: 41.
36 Carmel D, Roitman H, Yom-Tov E. On the relationship between novelty and popularity of user-generated content[J]. ACM Transactions on Intelligent Systems and Technology, 2012, 3(4): Article No.69.
37 钱佳佳, 罗卓然, 陆伟. 基于问题-方法组合的科技论文新颖性度量与创新类型识别[J]. 图书情报工作, 2021, 65(14): 82-89.
38 Piwowar H. Value all research products[J]. Nature, 2013, 493(7431): 159.
39 Davis A P, Grondin C J, Lennon-Hopkins K, et al. The comparative toxicogenomics database’s 10th year anniversary: update 2015[J]. Nucleic Acids Research, 2015, 43: D914-D920.
40 Davis A P, Wiegers T C, Wiegers J, et al. CTD tetramers: a new online tool that computationally links curated chemicals, genes, phenotypes, and diseases to inform molecular mechanisms for environmental health[J]. Toxicological Sciences, 2023, 195(2): 155-168.
41 Bateman T S, Hess A M. Different personal propensities among scientists relate to deeper vs. broader knowledge contributions[J]. Proceedings of the National Academy of Sciences of the United States of America, 2015, 112(12): 3653-3658.
42 Tacke E, Kupferschmied C, Lang D. Hypertrophe kardiomyopathie unter ACTH-behandlung[J]. Klinische P?diatrie, 1983, 195(2): 124-128.
43 Chariot P, Bonne G, Authier F J, et al. Expression of cytochrome c oxidase subunits encoded by mitochondrial or nuclear DNA in the muscle of patients with zidovudine myopathy[J]. Journal of the Neurological Sciences, 1994, 125(2): 190-193.
44 Yamauchi H, Aminaka Y, Yoshida K, et al. Evaluation of DNA damage in patients with arsenic poisoning: urinary 8-hydroxydeoxyguanine[J]. Toxicology and Applied Pharmacology, 2004, 198(3): 291-296.
45 Wong C C, Martincorena I, Rust A G, et al. Inactivating CUX1 mutations promote tumorigenesis[J]. Nature Genetics, 2014, 46(1): 33-38.
46 Hou J H, Ye J T. Are uncited papers necessarily all nonimpact papers? A quantitative analysis[J]. Scientometrics, 2020, 124(2): 1631-1662.
47 汪雪锋, 于慧妍, 郑思佳, 等. 学术论文创新质量评价研究——以多能干细胞技术为例[J]. 数据分析与知识发现, 2024, 8(5): 127-138.
48 H1 Connect[DS/OL]. [2024-07-10]. https://archive.connect.h1.co/search.
49 Bornmann L. Interrater reliability and convergent validity of F1000Prime peer review[J]. Journal of the Association for Information Science and Technology, 2015, 66(12): 2415-2426.
50 Praus P. Analysis of journal rankings confirms that more cited articles contain more references[J]. Scientometrics, 2024, 129(11): 7153-7160.
51 Golosovsky M, Larivière V. Uncited papers are not useless[J]. Quantitative Science Studies, 2021, 2(3): 899-911.