The distribution of references across texts: Some implications for citation analysis

In citation network analysis, complex behavior is reduced to a simple edge, namely, node A cites node B. The implicit assumption is that A is giving credit to, or acknowledging, B. It is also the case that the contributions of all citations are treated equally, even though some citations appear multiply in a text and others appear only once. In this study, we apply text-mining algorithms to a relatively large dataset (866 information science articles containing 32,496 bibliographic references) to demonstrate the differential contributions made by references. We (1) look at the placement of citations across the different sections of a journal article, and (2) identify highly cited works using two different counting methods (CountOne and CountX). We find that (1) the most highly cited works appear in the Introduction and Literature Review sections of citing papers, and (2) the citation rankings produced by CountOne and CountX differ. That is to say, counting the number of times a bibliographic reference is cited in a paper rather than treating all references the same no matter how many times they are invoked in the citing article reveals the differential contributions made by the cited works to the citing paper.     

Microsoft Academic automatic document searches: Accuracy for journal articles and suitability for citation analysis

Microsoft Academic is a free academic search engine and citation index that is similar to Google Scholar but can be automatically queried. Its data is potentially useful for bibliometric analysis if it is possible to search effectively for individual journal articles. This article compares different methods to find journal articles in its index by searching for a combination of title, authors, publication year and journal name and uses the results for the widest published correlation analysis of Microsoft Academic citation counts for journal articles so far. Based on 126,312 articles from 323 Scopus subfields in 2012, the optimal strategy to find articles with DOIs is to search for them by title and filter out those with incorrect DOIs. This finds 90% of journal articles. For articles without DOIs, the optimal strategy is to search for them by title and then filter out matches with dissimilar metadata. This finds 89% of journal articles, with an additional 1% incorrect matches. The remaining articles seem to be mainly not indexed by Microsoft Academic or indexed with a different language version of their title. From the matches, Scopus citation counts and Microsoft Academic counts have an average Spearman correlation of 0.95, with the lowest for any single field being 0.63. Thus, Microsoft Academic citation counts are almost universally equivalent to Scopus citation counts for articles that are not recent but there are national biases in the results.     

A systematic empirical comparison of different approaches for normalizing citation impact indicators

We address the question how citation-based bibliometric indicators can best be normalized to ensure fair comparisons between publications from different scientific fields and different years. In a systematic large-scale empirical analysis, we compare a traditional normalization approach based on a field classification system with three source normalization approaches. We pay special attention to the selection of the publications included in the analysis. Publications in national scientific journals, popular scientific magazines, and trade magazines are not included. Unlike earlier studies, we use algorithmically constructed classification systems to evaluate the different normalization approaches. Our analysis shows that a source normalization approach based on the recently introduced idea of fractional citation counting does not perform well. Two other source normalization approaches generally outperform the classification-system-based normalization approach that we study. Our analysis therefore offers considerable support for the use of source-normalized bibliometric indicators.     

Patent citation inflation: The phenomenon,its measurement,and relative indicators to temper its effects

In recent decades, the United States Patent and Trademark Office (USPTO) has been granting more and more patents with more and more references, which has led to patent citation inflation. Citation counts are a fundamental consideration in decisions about research funding, academic promotions, commercializing IP, investing in technologies, etc. With so much at stake, we must be sure we are valuing citations at their true worth. In this article, we reveal two types of patent citation inflation and analyze its causes and cumulative effects. Further, we propose some alternative indicators that more accurately reflect the true worth of a citation. A case study on the patents held by eight universities demonstrates that the relative indicators outlined in this paper are an effective way to account for citation inflation as an alternative approach to evaluating patent activity.     

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”.     

On the relationship between download and citation counts: An introduction of Granger-causality inference

Studies on the relationship between the numbers of citations and downloads of scientific publications is beneficial for understanding the mechanism of citation patterns and research evaluation. However, seldom studies have considered directionality issues between downloads and citations or adopted a case-by-case time lag length between the download and citation time series of each individual publication. In this paper, we introduce the Granger-causal inference strategy to study the directionality between downloads and citations and set up the length of time lag between the time series for each case. By researching the publications on the Lancet, we find that publications have various directionality patterns, but highly cited publications tend to feature greater possibilities to have Granger causality. We apply a step-by-step manner to introduce the Granger-causal inference method to information science as four steps, namely conducting stationarity tests, determining time lag between time series, establishing cointegration test, and implementing Granger-causality inference. We hope that this method can be applied by future information scientists in their own research contexts.     

On the relationships between bibliographic characteristics of scientific documents and citation and Mendeley readership counts: A large-scale analysis of Web of Science publications

In this paper we present a first large-scale analysis of the relationship between Mendeley readership and citation counts with particular documents’ bibliographic characteristics. A data set of 1.3 million publications from different fields published in journals covered by the Web of Science (WoS) has been analyzed. This work reveals that document types that are often excluded from citation analysis due to their lower citation values, like editorial materials, letters, news items, or meeting abstracts, are strongly covered and saved in Mendeley, suggesting that Mendeley readership can reliably inform the analysis of these document types. Findings show that collaborative papers are frequently saved in Mendeley, which is similar to what is observed for citations. The relationship between readership and the length of titles and number of pages, however, is weaker than for the same relationship observed for citations. The analysis of different disciplines also points to different patterns in the relationship between several document characteristics, readership, and citation counts. Overall, results highlight that although disciplinary differences exist, readership counts are related to similar bibliographic characteristics as those related to citation counts, reinforcing the idea that Mendeley readership and citations capture a similar concept of impact, although they cannot be considered as equivalent indicators.     

专利计量的概念、指标及实证——以全球有机电激发光技术相关专利为例

专利计量虽然在1994年才被提出,但是其在经济学、科学计量学等领域产生了广泛的影响.本文试图通过从宏观、中观、微观三个层次分别构建了专利计量的指标体系,并通过对全球有机电激发光技术领域的相关专利进行了详细地计量分析研究,主要对该领域机构进行了综合评价,分析了其年代分布、国际专利号分布、高被引专利分布等方面,并且对拥有高被引专利的机构进行了共引分析和可视化分析.得出该领域最具竞争力的研究机构、最早的公开专利、在中国的专利布局、研究机构之间相互关系等结论和启示.希望本文以对我国专利计量研究提供有益的参考.     

链接分析工具——博客链接索引(BSI)的功能与应用

针对自形开发的链接分析工具——博客链接索引（BSI）的功能与应用,描述开发BSI的背景、理论基础、数据库结构设计等;以演示的方式介绍BSI的查询与统计两大功能;分析BSI的应用范围,包括网络计量学、数据挖掘、搜索引擎等方面。     

The Citation Cloud of a biomedical article: a free,public, web-based tool enabling citation analysis

Background:An article''s citations are useful for finding related articles that may not be readily found by keyword searches or textual similarity. Citation analysis is also important for analyzing scientific innovation and the structure of the biomedical literature. We wanted to facilitate citation analysis for the broad community by providing a user-friendly interface for accessing and analyzing citation data for biomedical articles.Case Presentation:We seeded the Citation Cloud dataset with over 465 million open access citations culled from six different sources: PubMed Central, Microsoft Academic Graph, ArnetMiner, Semantic Scholar, Open Citations, and the NIH iCite dataset. We implemented a free, public extension to PubMed that allows any user to visualize and analyze the entire citation cloud around any paper of interest A: the set of articles cited by A, those which cite A, those which are co-cited with A, and those which are bibliographically coupled to A.Conclusions:Citation Cloud greatly enables the study of citations by the scientific community, including relatively advanced analyses (co-citations and bibliographic coupling) that cannot be undertaken using other available tools. The tool can be accessed by running any PubMed query on the Anne O''Tate value-added search interface and clicking on the Citations button next to any retrieved article.     

Technological opportunity discovery for technological convergence based on the prediction of technology knowledge flow in a citation network

As technological convergence has recently become a mainstream innovation trend, technological opportunities need to be explored in heterogeneous technology fields. Most of the previous convergence studies have taken a retrospective view in measuring the degree of convergence and monitoring the converging trends. This paper proposes a quantitative future-oriented approach to technological opportunity discovery for convergence using patent information. In a future-oriented approach, technological opportunities for convergence are suggested by predicting potential technological knowledge flows (TKFs) between heterogeneous fields. The potential TKFs are predicted by a link prediction method in a directed network, which is suggested in this paper to represent the direction of the predicted TKFs by adapting the concept of bibliographic coupling and edge-betweenness centrality. Converging technological opportunities are proposed as incremental and radical technological opportunities by extracting the potential increased knowledge flow links and emerging knowledge flow links. Moreover, the direction and themes of the predicted potential TKFs are provided as technological opportunities for convergence. As an illustration of the proposed method, the technological opportunities between biotechnology (BT) and information technology (IT) are explored. Firms and researchers can use the proposed method to seek out new technological opportunities from various technologies so that R&D policymakers can plan new R&D projects on technological convergence.     

Graph-based data mining: A new tool for the analysis and comparison of scientific domains represented as scientograms

The creation of some kind of representations depicting the current state of Science (or scientograms) is an established and beaten track for many years now. However, if we are concerned with the automatic comparison, analysis and understanding of a set of scientograms, showing for instance the evolution of a scientific domain or a face-to-face comparison of several countries, the task is titanically complex as the amount of data to analyze becomes huge and complex. In this paper, we aim to show that graph-based data mining tools are useful to deal with scientogram analysis. Subdue, the first algorithm proposed in the graph mining area, has been chosen for this purpose. This algorithm has been customized to deal with three different scientogram analysis tasks regarding the evolution of a scientific domain over time, the extraction of the common research categories substructures in the world, and the comparison of scientific domains between different countries. The outcomes obtained in the developed experiments have clearly demonstrated the potential of graph mining tools in scientogram analysis.     

引文内容分析视角下中文造假论文被引分析——以国家自然科学基金委员会查处的造假论文为例

以国家自然科学基金委员会查处的中文造假论文为例,基于引文内容分析其被其他文献引用的情况。调查表明:11篇中文造假论文共被有效引用34次;在定性为造假论文前被引用26次(占76.47%),在定性为造假论文后被引用8次(占23.53%,其中1次为负面引用);从引用情感来看,15次(占44.12%)为正面引用,18次(占52.94%)为中性引用,1次(占2.94%)为负面引用。建议加强发现造假论文的机构(个人)、作者单位与学术期刊等的沟通交流,督促造假论文尽快被撤销并在撤销声明中阐述具体原因;基于科学研究不断发展的特点以及学术不端行为长期存在的现状,科研工作者应具备质疑精神,对前人的研究结果进行借鉴和识别;关注造假论文的正面引用,应警惕连环造假行为。     

单篇文献的引文计量指标与Altmetrics的比较分析——以ESI的HotPapers为例

通过选取不同的数据源和分析方法探究Altmetrics文献计量方式对传统的引文计量方式的影响,以及这些计量指标如何评价单篇论文的影响力。结合ESI数据库热点文章的被引频次与Scopus平台提供的Altmetrics各项计量指标,尝试利用SPSS统计软件来分析传统的引文评价指标与Altmetrics各评价指标之间的相关性和差异性。通过研究分析发现:以引文为评价基础的ESI热点文章并不一定对应Altmetrics的高分值文献;进一步的研究从评价论文影响力的5个指标中简化为2个公因子——社交传媒因子和学术引用因子,可从不同群体对文献的不同传播利用方式来评价一篇论文的影响力;不同出版模式的文献在各评价指标上也有显著的差异。     

The system of measurable indicators for scientific and technological development of the Russian Federation: methodology and design

The vectors for the transformation of scientific-technological and industrial policy pursued by industrially developed countries in the post-crisis period between 2011 and 2016 are analyzed. It is shown that the economic reindustrialization strategy has been selected by the United States and the European Union as the main vector for the modernization of scientific and technological policy, limiting the export of the most advanced breakthrough technologies outside the leading countries. It is argued that the scientific and technological internationalization trend has been increasingly replaced by the policy of “technological colonization.” A system of measurable indicators for scientific and technological areas is proposed. It allows one to compare, rank, and justifiably select the most promising scientific and technological areas for the development of new industries in the Russian Federation involving minimum risks and barriers. The results of the testing of the system are presented. Using the system of measurable indicators is expected to provide evidence for decision making for concentrating intellectual, financial, organizational, and infrastructural resources on the development of priority areas that are key to addressing the large challenges facing the Russian Federation.     

The overlooked citations: Investigating the impact of ignoring citations to published patent applications

A utility patent application may result in two citable documents: a published patent application (PPA) and a patent if the application is granted. Most analytic works consider only citations to the patent and ignore those to the PPA. This study gathers more than 270,000 U.S. utility patents granted in 2014 and their PPAs, and compares their citation counts up to 2018. Statistics show that citations to patents, on the average, account for less than 50 % of those to the patents and their PPAs combined together, indicating a significant underestimation to the value or impact of the patents. The degree of depreciation is worse when the time gaps between patents and their PPAs are longer, as the PPAs not only have accumulated citations for a longer period, but also individually, concurrently, and continuously receive citations after the patent is granted. This study further applies Main Path Analysis to a conventional citation network involving only citations to the patents and another network augmented with those to the PPAs, using empirical data from United States Patent and Trademark Office (USPTO) Cancer Moonshot Patent Data. The main path derived from the augmented network is almost entirely different from that of the conventional network.     

从学科和期刊的引证视角看交叉学科的知识结构和演化问题——以图书情报学科为例的实证研究

[目的/意义]随着信息技术的高速发展,学科之间的交叉融合趋势越来越明显,探索学科间知识交流活动,明确学科结构,对其学科发展具有重要意义。以图书情报学科为例,观察其知识的流入与输出情况,包括知识从哪个学科哪些方面流入以及输出到哪些学科哪些方面。[方法/过程]选择图书情报领域12种核心期刊作为数据来源,以CNKI的学科分类为标准进行学科划分,使用可视化软件工具Gephi,从参考和引证两个角度探讨图书情报学科与其他学科间的交叉融合情况。[结果/结论]图书情报学科与计算机科学、基础科学综合、经济管理等学科联系紧密,学科结构趋于稳定;图书情报学科的参考总量远远小于被引总量;自引率呈逐年下降趋势,和外部学科交流频繁。     

The European Union,China, and the United States in the top-1% and top-10% layers of most-frequently cited publications: Competition and collaborations

The percentages of shares of world publications of the European Union and its member states, China, and the United States have been represented differently as a result of using different databases. An analytical variant of the Web-of-Science (of Thomson Reuters) enables us to study the dynamics in the world publication system in terms of the field-normalized top-1% and top-10% most-frequently cited publications. Comparing the EU28, USA, and China at the global level shows a top-level dynamic that is different from the analysis in terms of shares of publications: the United States remains far more productive in the top-1% of all papers; China drops out of the competition for elite status; and the EU28 increased its share among the top-cited papers from 2000 to 2010. Some of the EU28 member states overtook the United States during this decade; but a clear divide remains between EU15 (Western Europe) and the Accession Countries. Network analysis shows that China was embedded in this top-layer of internationally co-authored publications. These publications often involve more than a single European nation.