共查询到20条相似文献，搜索用时 31 毫秒
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This study investigates the use, citation and diffusion of three bibliometric mapping software tools (CiteSpace, HistCite and VOSviewer) in scientific papers. We first conduct a content analysis of a sample of 481 English core journal papers—i.e., papers from journals deemed central to their respective disciplines—in which at least one of these tools is mentioned. This allows us to understand the predominant mention and citation practices surrounding these tools. We then employ several diffusion indicators to gain insight into the diffusion patterns of the three software tools. Overall, we find that researchers mention and cite the tools in diverse ways, many of which fall short of a traditional formal citation. Our results further indicate a clear upward trend in the use of all three tools, though VOSviewer is more frequently used than CiteSpace or HistCite. We also find that these three software tools have seen the fastest and most widespread adoption in library and information science research, where the tools originated. They have since been gradually adopted in other areas of study, initially at a lower diffusion speed but afterward at a rapidly growing rate. 相似文献
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[目的/意义]基于科学论文发表后的早期特征,准确预测论文未来的引文扩散演变模式,对科学产出评估、科学突破早期发现等都具有潜在的价值。[方法/过程]归纳总结9种不同的引文扩散演变模式,并基于论文自发表后的早期时序、结构和文献特征,建模预测未来一定引文窗口内的演变模式。选择美国物理学会的引文数据集进行实证研究,探究不同特征组合下引文扩散演变模式的预测效果。[结果/结论]结果显示,时序特征对预测模型的贡献程度最大,同时结构特征和文献特征也起到重要的作用,当融合3个特征时所有预测模型的准确率均超过了80%,证明了本文所选特征的有效性。 相似文献
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《Journal of Informetrics》2022,16(4):101342
Inspired by “sleeping beauties in science”, we proposed that the awakening effect in knowledge diffusion is ubiquitous, whereas the “prince” paper has the strongest effect. To test this hypothesis, a three-layer super-network model depicting the knowledge diffusion trajectory is designed and the diffusion path of the awakening effect (defined on the basis of influential strength) is simulated. In detail, the model is built based on the citation network and collaboration network of 63785 publications in the library and information science domain. Through meta-paths in this super-network, the influential strength of a paper and the awakening effect from neighboring papers can be quantified into 36 numerical features. By testing the effectiveness of these features in citation counts prediction, we try to prove our hypothesis. Thus an effective predictor in machine learning is trained upon these features. Using this predictor, we showed that most neighboring papers in the super-network had effects on future citation counts. The effectiveness of these features is again demonstrated through experiments on papers with different publication years. We also did a case study on papers that were significantly affected by the awakening effect, and found that the model proposed in this paper can also be used to explain some common phenomena in knowledge diffusion. All results show that the awakening effect could be not only ubiquitous but also quantifiable. 相似文献
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This paper suggests a new scientometric index that estimates knowledge diffusion and has two constituents: the first one is equivalent to a usual citation index, i.e., it describes the visible diffusion of scientific knowledge; the second one reflects the implicit diffusion of scientific knowledge and is expressed through the number of implicit citations. The practical value of the suggested index is that it permits implicit initiators of the scientific mainstream to be easily identified. The distinctive feature of such scientists is the large value of the suggested citation index and the low value of the usual citation index. 相似文献
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《Journal of Informetrics》2014,8(3):594-605
This study presents a unique approach in investigating the knowledge diffusion structure for the field of data quality through an analysis of the main paths. We study a dataset of 1880 papers to explore the knowledge diffusion path, using citation data to build the citation network. The main paths are then investigated and visualized via social network analysis. This paper takes three different main path analyses, namely local, global, and key-route, to depict the knowledge diffusion path and additionally implements the g-index and h-index to evaluate the most important journals and researchers in the data quality domain. 相似文献
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《Journal of Informetrics》2023,17(1):101381
Main path analysis (MPA) is an effective method widely accepted in science and technology for extracting knowledge diffusion paths. Traditional citation analysis assumes that all citations are treated equally. In contrast, this paper proposes a new MPA framework from the perspective of citation structure and content. Three indicators are considered to adjust edge weight: (1) Structural similarity, (2) Topic similarity and (3) Sentiment analysis. This study takes the bullwhip effect and the Internet of Things domain as examples to verify the reliability and feasibility of improved MPA. The results show that the improved main path uncovers the knowledge trajectories appropriately, which has an ability to distinguish citations and detect important papers. This research enriches MPA theory and provides future research directions from perspective of citation structure and content. 相似文献
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科学知识借助引用关系发生动态扩散,客观记录科学发展与演化的轨迹。由于知识之间存在千丝万缕的联系,以孤立的观点看待科学知识的影响与价值往往得到的是片面的感观。本文从联系的视角观察科学知识产出,尝试通过被引、引用、文献耦合与共被引等文献关系为单篇论著构建引文扩散网络,探讨"文献嵌入网络"的概念、测度方式及其在引文扩散过程中起到的特殊作用。案例分析显示,科学知识的形成相伴于科学知识网络的发展,同时也受到这个网络的影响:科学知识向科学领域的扩散,遵循从核心领域向周边领域的扩散模式;施引文献可以揭示目标文献中没有显式呈现的信息;四种文献关系之间可能存在相当程度的重合,引文扩散过程显示出知识的"黏滞性"与非常明显的"小世界"特征。对科学产出的扩散网络进行量化有助于为全面评价其价值提供更多客观依据。 相似文献
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高Altmetrics指标科技论文学术影响力研究 总被引：9，自引：0，他引：9
引入"公平性测试"方法以消除时间窗口对被引次数的影响。以高Altmetrics指标论文作为样本,选取与样本论文发表在同一期刊同一期上前后两篇论文作为参照。利用Altmetric.com、Web of Science分别获取273篇样本及参照论文的Altmetric分数、底层数据值和被引用次数。通过比较分析后发现:Altmetrics和引文数两种指标反映出读者对文献的不同关注方向,底层数据源中大众媒体对于Altmetric分数的影响最明显,高Altmetrics指标论文同时具有较高的学术影响力。作为一种早期指标,高Altmetrics指标在一定程度上能够被视作文章在未来获得高被引的风向标。 相似文献
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［目的/意义］ 基于专利的全代引证网络对专利进行分类,对高影响力专利的知识扩散特征进行分析,为专利影响力的认识和评估提供重要参考。［方法/过程］ 以生物学家悉尼·布伦纳的专利为例,研究其专利和前向引证专利生成的专利全代引证网络,根据专利的直接引证数量和引证长度两个对专利扩散发挥重要作用的因素将专利分为四类,将具有高被引数量长引证路径的专利定义为高影响力专利,对这种专利的知识扩散特征进行分析。［结果/结论］ 研究发现,在专利的全代引证网络中"关键专利""重要专利"和"隐藏的高影响力专利"对专利的扩散影响巨大,全代引证网络中专利的领域变化也体现了知识的流动现象,知识扩散速度可以通过数字直接刻画专利时序网络特点。结合研究结果,对高影响力专利的特点有了更具体的认识,并为高影响力专利的评价提出新的思路。 相似文献
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学术创新的扩散过程研究 总被引：2，自引：2，他引：0
知识扩散能促进知识创新,从过程而非结果的视角研究学术创新的扩散,能够还原学术发展的轨迹,为学术研究及科研管理提供可靠依据。本文选取结构洞理论为学术创新实例,采用包含时间维度的扩散理论和分析时间流的主路径分析方法进行创新扩散实证研究。通过建立扩散时序网络,分析扩散曲线、路径与关键节点和学科分布与信息交互模式,定义扩散广度、速度、强度及延时,并进行测度,认为可将创新扩散过程研究归纳为五个步骤,其内容涵盖研究方法与分析维度、分析层次和分析视角的整合。 相似文献
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在系统梳理“以刊评文”的由来和成因的基础上,提出了“以刊评文”的危害,包括:1)以SCI为导向,损伤科研生态;2)优秀科技论文外流,知识产权割让;3)科研方向跟从,应用价值不高;4)期刊竞争不平等,有碍国内科技期刊发展。阐释了以建立健全同行评议为核心的应对策略:1)建立小同行专家库,实行分类分领域评价;2)优化同行评议生态,提升专家评审素质和环境;3)建立国家开放知识库和预印本平台,推进开放评审与开放获取相结合的公开机制;4)建立有国际影响力的论文引文索引数据库,完善自身评价手段和工具。 相似文献
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The scientific impact of a publication can be determined not only based on the number of times it is cited but also based on the citation speed with which its content is noted by the scientific community. Here we present the citation speed index as a meaningful complement to the h index: whereas for the calculation of the h index the impact of publications is based on number of citations, for the calculation of the speed index it is the number of months that have elapsed since the first citation, the citation speed with which the results of publications find reception in the scientific community. The speed index is defined as follows: a group of papers has the index s if for s of its Np papers the first citation was at least s months ago, and for the other (Np ? s) papers the first citation was ≤s months ago. 相似文献
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[目的/意义] 论文引用专利的“反向引用”也是科学与技术知识关联的重要体现。针对现有“反向引用”研究的不足,分析中国专利技术对世界科学研究的影响。[方法/过程] 搜集整理中国专利被世界科学论文引用的数据,利用文献计量学方法分析“反向引用”的引用频数、技术关联度、引用时滞及技术循环周期等指标,利用社会网络分析方法构建“反向引用”网络,探讨技术领域到科学领域的知识流动情况。[结果/结论] 中国专利技术对世界科学研究的影响力越来越大。科学与技术的双向互动在化学领域体现的最为明显,化学、工程、材料科学三个学科领域较多地吸收了专利知识,技术关联度较高。前1-4年的技术对当前科学影响最大,中国专利被科学文献引用的循环周期较短,平均为4.69年。 相似文献
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学术论文是科研活动产出和知识信息交流的主要载体,而学术论文被引用则是学术成果获得认同的主要方式之一。研究高被引论文所引用论文的分布特征,对于了解高被引论文知识基础的构成具有重要意义。本文以ISI图书情报学（Information Science & Library Science）为例,以实证研究为基础,按比例采集图书情报学领域的高被引论文数据,查询这些高被引论文的参考文献的被引频次数据,以期得到高被引论文的引证特点。研究发现,图书情报学领域的高被引论文更多地引用了高被引参考文献;随着被引频次的降低,其引用的高被引论文所占的比例也在下降。 相似文献
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[目的/意义]采用被引次数衡量学术论文影响力存在诸多弊端。本文认为学术论文影响力包括其传播的深度、速度和广度3个方面，熵可用于衡量学术论文影响力传播的广度。[方法/过程]选择1901-2017年生物医学领域的诺贝尔奖论文作为最具影响力的论文纳入实验组，并根据1：1配对原则设立对照组，比较两组论文发表后5年内其施引文献所属学科数量、熵以及熵与被引次数的相关性。[结果/结论]实验组中65%以上的论文施引文献学科数量高于对照组；实验组熵的均值介于0.552-0.772，对照组介于0.251-0.481，有显著性差异（P<0.05）；两组论文的被引次数与熵的相关性较弱，均小于0.3。结果表明：①70%以上的高影响力论文在发表早期能够影响较多的学科；②采用熵对论文影响力广度进行识别具有可行性。 相似文献
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《Journal of Informetrics》2019,13(4):100977
Main path analysis is a popular method for extracting the backbone of scientific evolution from a (paper) citation network. The first and core step of main path analysis, called search path counting, is to weight citation arcs by the number of scientific influence paths from old to new papers. Search path counting shows high potential in scientific impact evaluation due to its semantic similarity to the meaning of scientific impact indicator, i.e. how many papers are influenced to what extent. In addition, the algorithmic idea of search path counting also resembles many known indirect citation impact indicators. Inspired by the above observations, this paper presents the FSPC (Forward Search Path Count) framework as an alternative scientific impact indicator based on indirect citations. Two critical assumptions are made to ensure the effectiveness of FSPC. First, knowledge decay is introduced to weight scientific influence paths in decreasing order of length. Second, path capping is introduced to mimic human literature search and citing behavior. By experiments on two well-studied datasets against two carefully created gold standard sets of papers, we have demonstrated that FSPC is able to achieve surprisingly good performance in not only recognizing high-impact papers but also identifying undercited papers. 相似文献
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[目的/意义] 研究Altmetrics热点论文的传播特性,阐释学术内容的学术影响力和社会影响力。[方法/过程] 以www.altmetric.com热点论文的数据为基础,双向分析热点论文的Altmetrics分值与Web of Science被引次数的相关性,并讨论其传播渠道的多样性、传播主体的分布以及学术内容在社交媒体的传播影响。[结果/结论] 学科的差异影响Altmetrics与传统引文分析的相关性。公众为学术内容社交传播的主体,科学家利用社交媒体推广学术内容的比例呈逐年增长趋势。热点论文在Twitter上的传播一般在10-30d达到峰值,影响其传播的因素主要包括：学术传播内容的显著性和新奇性、学术传播的内需、开放获取、学术内容的营销途径等。虽然Altmetrics有速度和广度的优势,但也存在理论方法缺失、认知程度不高、数据质量较低、商业驱动浓厚、容易博弈等缺点。 相似文献
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随着交叉科学研究在促进社会发展重大综合性问题解决方面的优势逐渐凸显,越来越多的国家对交叉科学研究给予高度的重视与支持,如何对交叉科学的研究成果进行有效的鉴定与评估也成为科技管理部门亟待解决的重要问题。本文在传统引文指标的基础上,引入PLoS官方平台的使用数据(html浏览、xml下载及pdf下载)作为补充,综合评价交叉科学研究成果的影响力情况。以2009-2013年发表在开源期刊PLoS Computational Biology的研究论文为例,研究结果表明:(1)学科交叉水平与论文影响力之间存在一定的正向关系,学科交叉水平高的论文,对应的使用数据与引用数据要明显高于学科交叉水平较低的论文;(2)论文的使用数据与引用数据相互促进,在引用数据达到峰值时,对应的使用数据也会随之出现一定的回升;(3)学科交叉程度对使用数据与引用数据之间的相关关系也有较为显著的影响。本文从使用数据和引用数据两个维度探索交叉科学研究成果的影响力,为当前交叉科学研究成果影响力的评价提供了新的借鉴与参考。 相似文献
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科学知识扩散研究框架 总被引：2，自引：1，他引：1
通过对科学知识扩散相关文献的梳理,构建科学知识扩散的研究框架,并对研究对象、扩散关系表示、衡量指标、扩散模型等方面进行详细评述。扩散的对象包括期刊、学科、科研人员等,扩散过程主要以文献引证和作者合著关系表示。在实证中,基于文献引证关系的引文及引文网络分析是科学知识扩散的主流研究方法。衡量指标可以按照测度粒度分为文章、期刊、学科3个层次。现有科学知识扩散的模型研究以定性研究为主,定量化分析较少,常见思路为跨学科借鉴成熟模型。 相似文献