共被引网络中介中心性的Zipf-Pareto分布研究

针对共被引网络的统计特性的研究,以科学计量学领域的权威期刊《科学计量学》(Scientometrics)为数据来源,建立共被引网络,明确了《科学计量学》(Scientometrics)中高被引文献与高中心性引文的特点;以该共被引网络为例,应用复杂网络分析方法,分析了共被引网络的统计特性,包括度分布、中介中心性的分布等。结果表明共被引网络是一个具有小世界、无标度特性的复杂网络;中介中心性的分布符合Zipf-Pareto分布;而且只有少部分引文节点具有高中介中心性的值,多数引文节点的中介中心性值都很小。     

Challenges of measuring software impact through citations: An examination of the lme4 R package

The rise of software as a research object is mirrored by increasing interests in quantitative studies of scientific software. However, inconsistent citation practices have led most existing studies of this type to base their analysis of software impact on software name mentions, as identified in full-text publications. Despite its limitations, citation data exists in much greater quantities and covers a broader array of scientific fields than full-text data, and thus can support investigations with much wider scope. This paper aims to analyze the extent to which citation data can be used to reconstruct the impact of software. Specifically, we identify the variety of citable objects related to the lme4 R package and examine how the package’s impact is dispersed across these objects. Our results shed light on a little-discussed challenge of using citation data to measure software impact: even within the category of formal citation, the same software object might be cited in different forms. We consider the implications of this challenge and propose a method to reconstruct the impact of lme4 through its citations nonetheless.     

Combining mapping and citation network analysis for a better understanding of the scientific development: The case of the absorptive capacity field

The general aim of this paper is to show the results of a study in which we combined bibliometric mapping and citation network analysis to investigate the process of creation and transfer of knowledge through scientific publications. The novelty of this approach is the combination of both methods. In this case we analyzed the citations to a very influential paper published in 1990 that contains, for the first time, the term Absorptive Capacity. A bibliometric map identified the terms and the theories associated with the term while two techniques from the citation network analysis recognized the main papers during 15 years. As a result we identified the articles that influenced the research for some time and linked them into a research tradition that can be considered the backbone of the “Absorptive Capacity Field”.     

The many facets of academic mobility and its impact on scholars' career

International mobility in academia can enhance the human and social capital of researchers and consequently their scientific outcome. However, there is still a very limited understanding of the different mobility patterns among scholars with various socio-demographic characteristics. By studying these differences, we can detect inequalities in access to scholarly networks across borders, which can cause disparities in scientific advancement. The aim of this study is twofold. First, we investigate to what extent individuals’ factors (e.g., country, career stage, and field of research) associate with the mobility of male and female researchers. Second, we explore the relationship between mobility and scientific activity and impact. For this purpose, we used a bibliometric approach to track the mobility of authors. To compare the researchers’ scientific outcomes, we considered the number of publications and received citations as indicators, as well as the number of unique co-authors in all their publications. We also analyzed the co-authorship network of researchers and compared centrality measures of “mobile” and “non-mobile” researchers. Results show that researchers from North America and Sub-Saharan Africa, particularly female ones, have the lowest, respectively, highest tendency towards international mobility. Having international co-authors increases the probability of international movement. Our findings uncover gender inequality in international mobility across scientific fields and countries. Across genders, researchers in the Physical sciences have the most and in the Social sciences the least rate of mobility. We observed more mobility for Social scientists at the advanced career stage, while researchers in other fields prefer to move at earlier career stages. Also, we found a positive correlation between mobility and scientific outcomes, but no apparent difference between females and males. Indeed, researchers who have started mobility at the advanced career stages had a better scientific outcome. Comparing the centrality of mobile and non-mobile researchers in the co-authorship networks reveals a higher social capital advantage for mobile researchers.     

PlumX评价指标对促进中国科技期刊国际传播的启示

利用各种社交网络平台,进行科学论文的获取、分享与传播已成为当前学术交流的重要形式,为此研究社交网络对科技期刊国际传播的影响。利用Elsevier数据库整合的替代计量学指标PlumX,分析PlumX与论文被引频次的关系及其学术特征。基于《中国天然药物》单刊及药理学/毒理学学科分析,均发现高被引论文的PlumX评分显著高于低被引论文,且学科高被引论文的被引频次和PlumX评分呈正相关,此外,高质量的综述和国际论文更易获得社交网络关注。研究结果发现PlumX指标能够对单篇论文的学术影响力进行快速评价,非国际权威期刊中的热点论文也可能获得较高关注,指出英文科技期刊应重视约组社交网络平台发达和应用广泛的相关主流国家优秀稿件,合理利用社交网络平台有助于获得较高的PlumX评分,进而提升发展中国家科学家的话语权。     

交叉科学成果影响力研究:使用数据与引用数据视角

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。     

基于关键词共现的可视化技术的精神病专科医院文献主题分析

应用关键词共现的方法对全国发文量居前5位的精神痛专科医院发表的论文进行关键词词频及共现关系分析,并采用社会网络分析软件Ucinet形成可视化的共现网络图,对文献的内容进行挖掘分析。发现这5家医院在精神疾病的研究方面的侧重点各有差异。     

Text Analysis in R

Computational text analysis has become an exciting research field with many applications in communication research. It can be a difficult method to apply, however, because it requires knowledge of various techniques, and the software required to perform most of these techniques is not readily available in common statistical software packages. In this teacher’s corner, we address these barriers by providing an overview of general steps and operations in a computational text analysis project, and demonstrate how each step can be performed using the R statistical software. As a popular open-source platform, R has an extensive user community that develops and maintains a wide range of text analysis packages. We show that these packages make it easy to perform advanced text analytics.     

论文学科交叉测度研究:从全部引文到章节引文

量化测度研究成果的学科交叉性是交叉科学研究中的重要问题,对于理解学科交叉现象与学科发展规律具有重要意义。基于引文关系的学科多样性测度是学科交叉测度的主流方法,现有的研究大多将论文的参考文献作为一个整体来探究论文的学科交叉程度,忽略了不同章节参考文献的分布、不同参考文献的重要程度以及相同参考文献的多次引用等情况。本文尝试基于论文中不同章节的引文标注位置来探究不同章节的学科交叉程度,进而根据不同章节参考文献的重要程度来计算论文的加权学科交叉度。以2007-2016年发表在PLoS ONE期刊上的研究论文为例,研究结果表明:(1)引言(Introduction)、讨论(Discussion)、方法(Method)和结果(Results)四个章节的学科交叉程度依次降低;(2)与基于整体参考文献的学科交叉测度相比,基于引文标注位置的加权学科交叉度数值相对较低且分布更为集中。基于引文标注位置的学科交叉测度方法可以从内容的微观层面更加细致地测度论文的学科交叉水平,为交叉科学研究成果的测度和高交叉研究成果的识别提供了新的视角与思路。     

Betweenness centrality as a driver of preferential attachment in the evolution of research collaboration networks

We analyze whether preferential attachment in scientific coauthorship networks is different for authors with different forms of centrality. Using a complete database for the scientific specialty of research about “steel structures,” we show that betweenness centrality of an existing node is a significantly better predictor of preferential attachment by new entrants than degree or closeness centrality. During the growth of a network, preferential attachment shifts from (local) degree centrality to betweenness centrality as a global measure. An interpretation is that supervisors of PhD projects and postdocs broker between new entrants and the already existing network, and thus become focal to preferential attachment. Because of this mediation, scholarly networks can be expected to develop differently from networks which are predicated on preferential attachment to nodes with high degree centrality.     

计量学视角下社群信息学研究的特征、轨迹及走向

利用信息可视化软件Citespace Ⅱ,以Web of Science(SCI,ISTP)中收录的1998-2011年间的521篇社群信息学相关文献及其所包含的17 968篇参考文献为研究对象,对发文时间、作者、机构、学科、参考文献等进行分析;同时通过对高频关键词和高中心度、高被引文献进行分析,明确社群信息学研究热点。结果显示,社群信息学研究还未迎来大发展时期,但知识储备速度在不断加快;社群信息学研究由社会网络和社会资本两个分支组成,其中,社会网络是主要分支;网络学习、社会网络、复杂网络、卫生保健将成为未来重点研究主题。     

我国高校科研合作网络的构建与特征分析-基于“211”高校的数据

[目的/意义]我国地域辽阔、高校众多,了解不同高校之间的科学合作现状,对于推进"2011计划"有着重要意义。以SCI和SSCI数据库中的全体数据作为数据来源,针对传统科学计量学方法和现有软件无法处理海量数据的问题,开发出全新的数据处理方法,用于实现对不同机构之间的论文合作分析。[方法/过程]以我国111所"211"高校作为研究对象,对主要研究型大学之间以SCI和SSCI论文为代表的高水平论文合作情况进行定量研究,计算各高校在论文合作网络中的中介中心性并排序,进而绘制合作网络图谱。[结果/结论]我国高校科研论文合作的现状与全貌是科研实力较强的"985"综合性高校排序靠前,而学科专业性较强、地理位置偏僻的高校排序靠后;我国目前的大学科学论文合作整体存在以地理聚类为主、学科聚类为辅的合作关系特征。这一特征为科研管理和教育管理工作提供了启示,即:既要发挥"985"高校的领军作用,也要发挥区域中优势高校的增长极作用,在"2011计划"的学科框架下实现广泛交流。     

基于微信平台的科技期刊学术论文推广分析——以《中国中药杂志》为例

为研究科技期刊学术论文通过微信推广的方式与效果,通过统计2020年《中国中药杂志》微信公众号上学术论文微信推广数据,分析相关不同类型文章的阅读数据,探索科技期刊推广学术论文并尽量实现最大传播效率应注意的因素。结果显示,《中国中药杂志》微信公众号对纸媒文章,尤其是全年24期封面推荐论文以及学术专题的微信推送数据效益较高,提示科技期刊选择微信公众号进行学术论文推广时注意符合平台的传播特点——紧跟行业热点、选择头条推送、优化标题及内容等,从而制作出有趣、有料的学术论文推广文案,推动期刊长远发展。     

搜索引擎日志挖掘领域的论文合著网络分析

基于Web of SCI和EI数据库中所收录的有关搜索引擎日志挖掘领域的研究论文,构建作者合著网络,利用社会网络分析方法研究合著网络的中心性、小世界特性、连通性等基本特征,发现该领域中最核心的科研合作团队、研究人员及其研究内容等。     

基于中心性分析的知识型员工对医药企业知识共享的影响

以案例分析的方式,采用网络中心性指标对员工知识共享意愿进行量化,构建知识量评价指标体系,采用yaahp6.0软件计算指标权重并分析两个因素之间的相关性,得出不同角色员工对企业内部知识共享的影响力。     

The lognormal distribution explains the remarkable pattern documented by characteristic scores and scales in scientometrics

Characteristic scores and scales (CSS) – a well-established scientometric tool for the study of citation counts – have been used to document a striking phenomenon that characterizes citation distributions at high levels of aggregation: irrespective of scientific field and citation window empirical studies find a persistent pattern whereby about 70% of scientific papers belong to the class of poorly cited papers, about 21% belong to the class of fairly cited papers, 6% to that of remarkably cited papers and 3% to the class of outstandingly cited papers. This article aims to advance the understanding of this remarkable result by examining it in the context of the lognormal distribution, a popular model used to describe citation counts across scientific fields. The article shows that the application of the CSS method to lognormal distributions provides a very good fit to the 70–21–6–3% empirical pattern provided these distributions are characterized by a standard deviation parameter in the range of about 0.8–1.3. The CSS pattern is essentially explainable as an epiphenomenon of the lognormal functional form and, more generally, as a consequence of the skewness of science which is manifest in heavy-tailed citation distributions.     

Examining the usage,citation, and diffusion patterns of bibliometric mapping software: A comparative study of three tools

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.     

C-index: A weighted network node centrality measure for collaboration competence

This paper proposes a new node centrality measurement index (c-index) and its derivative indexes (iterative c-index and c_g-index) to measure the collaboration competence of a node in a weighted network. We prove that c-index observe the power law distribution in the weighted scale-free network. A case study of a very large scientific collaboration network indicates that the indexes proposed in this paper are different from other common centrality measures (degree centrality, betweenness centrality, closeness centrality, eigenvector centrality and node strength) and other h-type indexes (lobby-index, w-lobby index and h-degree). The c-index and its derivative indexes proposed in this paper comprehensively utilize the amount of nodes’ neighbors, link strengths and centrality information of neighbor nodes to measure the centrality of a node, composing a new unique centrality measure for collaborative competency.     

WHO英文网站健康主题语义链接关系社会网络分析

选择世界卫生组织（WHO）网站健康信息主题作为研究对象,统计各个健康主题的互链数据,利用文本相似性算法并基于语义的角度,运用社会网络分析方法和Ucinet软件,从中心度、密度、凝聚子群角度分析这些健康主题之间的社会网络关系,最终证实挖掘的健康主题信息与2013年世界卫生报告中阐述的全民健康覆盖目标信息相匹配。