The citation impact of social sciences and humanities upon patentable technology

This paper examines the citation impact of papers published in scientific-scholarly journals upon patentable technology, as reflected in examiner- or inventor-given references in granted patents. It analyses data created by SCImago Research Group, linking PATSTAT’s scientific non-patent references (SNPRs) to source documents indexed in Scopus. The frequency of patent citations to journal papers is calculated per discipline, year, institutional sector, journal subject category, and for “top” journals. PATSTAT/Scopus-based statistics are compared to those derived from Web of Science/USPTO linkage. A detailed assessment is presented of the technological impact of research publications in social sciences and humanities (SSH). Several subject fields perform well in terms of the number of citations from patents, especially Library and Information Science, Language and Linguistics, Education, and Law, but many of the most cited journals find themselves in the interface between SSH and biomedical or natural sciences. Analyses of the titles of citing patents and cited papers are presented that shed light upon the cognitive content of patent citations. It is proposed to develop more advanced indicators of citation impact of papers upon patents, and ways to combine citation counts with citation content and context analysis.

     

A study on the citation situation within the citing paper: citation distribution of references according to mention frequency

Citation impact indicators play a significant role in evaluating the scientific research activity. Most of citation impact indicators are based on the citation count that the publication is cited as a reference in the other publications, but the difference between each citation situation was not considered. Normally, the number of citations that a publication is cited in the other publications may represent the formal quality of the publication. Similarly, the number of times that a publication is really mentioned within the citing publication, it may also represent the formal quality of the citation. We have examined about how many times each reference was really mentioned within the citing publications and studied about the citation situation within the citing publications. We verified that the citation distribution of references according to the mention frequency follows the Generalized Pareto distribution. The results showed that about 20% of total references were mentioned three and more times, and the number of citation mentions for the about 50% of total references were from about 20% of the total references in the citing publications.     

A quantitative analysis of determinants of non-citation using a panel data model

The term “non-citation factor” refers to the percentage of never-cited papers in a citation time window, a common phenomenon in the science world. Some scholars have qualitatively explored the reasons for not citing a publication, and quantitatively analyzed the mathematical functional relations between the “non-citation factor” and “impact factor of a journal.” This study simultaneously considers the mutual relations and closeness degree between the “non-citation factor” and different influencing factors from a novel perspective—that of using a more structuralized panel data model. The analysis revealed that the determinants, including “impact factor of journal,” “age of journal,” “average number of references per paper in journal,” and “issues of journal,” exerted an extremely small but positive influence (<?0.025) on the decline of “percentage of never-cited papers in the citation time window of publication year or 3 years.” That means the improvement of these determinants can decrease the percentage of never-cited papers. The “impact factor of the journal” always had the biggest positive influence, while the “average number of references per paper in journal” always had the smallest positive influence. In wider citation time windows of 3 or 6 years, two determinants—“number of publications in journal” and “amount of interdisciplinarity in journal”—began to exert a negative effect with a positive correlation coefficient on the decline of the “non-citation factor.” That means the improvement of these two determinants cannot decrease the value of the “non-citation factor,” even though they can increase its value. It is worth noting that the “impact factor of the journal” had a positive influence on the decline of the percentages of never-cited papers in the citation time window of publication year or 3 years, and began to play a negative role in the decline of percentage of never-cited papers in the citation time window of 6 years. Finally, three variables—“average number of authors per paper in journal,” “average number of references per paper in journal,” and “issues of journal”—no longer exerted an influence on the decline of percentages of never-cited papers in the citation time window of 6 years, while “age of journal” and “average number of pages per paper in journal” still made a positive contribution. Our findings could help research institutions, researchers, editors, and publishers understand the positively or negatively influential factors that lead to non-citation, thus improving the chance of papers being cited and having some academic influence.     

Citations: Indicators of significance?

What makes a scientific article significant? This paper-part of a larger study which will examine how various kinds of significance can be related to one another in a coherent theoretical framework-focusses on the processes by which new knowledge claims are being integrated into the cognitive structure when they are cited in other papers. Citations appear both as “threads” linking the citing papers to the existing literature in the field, and as elements fulfilling specific functions within the arguments made in these papers. We have found that (1) it is misleading to equate every article with a single knowledge claim, let alone with an attempt to construct “a fact”; (2) even when the same “sentence” is cited repeatedly, it can be put to quite different uses in the citing papers; and (3) the process of codification of scientific knowledge through the use of references appears to be far more complex and multi-dimensional than citation context analyses focussing on the use and the gradual disappearance of modalities would lead us to believe. Some consequences for the use use of citation analysis to reconstruct cognitive structures will be discussed.     

The Garfield impact factor, one of the fundamental indicators in scientometrics

The paper summarizes some basic features of the Garfield impact factor (GF). Accordingly, GF should be regarded as a scientometric indicator representing the relative contribution of journals to the total impact of information in a field. For calculating GF, both from theoretical and practical reasons the “ratio of the sums” method is recommended over the “mean of the ratios” method. Scientific advances are made by the most influential, presumably most frequently cited articles. The distribution of citations among the publications is skewed in journals. Consequently, the GF index will be influenced primarily by the highly cited papers. It follows, GF represents the most valuable part of the information in journals quantitatively, and even therefore it may be regarded as a reliable impact indicator.     

A comparison of citation contexts between natural sciences and social sciences and humanities

This study uses the method of citation context analysis to compare differences in citation contexts, including cited concepts and citation functions, between natural sciences (NS) and social sciences and humanities (SSH), based on articles citing Little Science, Big Science (LSBS) published between 1963 and 2010. The findings indicate that NS and SSH researchers frequently cite LSBS as a source that is related to a specific topic and as evidence to support a claim. No significant differences were identified in the distribution of cited concepts included in LSBS, but significant differences were observed in the reasons for citing LSBS between NS and SSH citing articles. However, reverse trends were observed in the percentage of some cited concepts and citation functions between NS and SSH, which implies that subtle differences in citation behavior exist between NS and SSH researchers. In addition, each concept category has a different half-life. Concepts related to characteristics of big science and scientific collaboration have the longest half-lives.     

Diversity of fields in patent citations: synchronic and diachronic changes

While there is a large body of research analyzing the overall structure of citation relations for patents, there has been very little research seeking to clarify the characteristics of fields relating to the diffusion of technology through observing the citation network surrounding each patent individually and tracing its growth. This study focused on the classifications assigned to patents and examined the diversity of the fields of patents citing each patent from the following two perspectives: (1) expected values for growth in the number of citing fields, when regarding the observation period as being in a synchronic state and assuming that the strength of connections between each patent and citing fields is constant; and (2) empirical values for growth in the number of citing fields according to the increase in the cumulative number of citations over time. From the results, it was confirmed that the strength of potential connections between each patent and citing fields changes over time. Especially in the fields of “chemistry; metallurgy” and “physics,” the following change is considerable: a patent tends to receive citations repeatedly from a limited range of fields for a while, but later comes to be cited by various fields.     

Citation context analysis of a co-citation cluster: Recombinant-DNA

The techniques of co-citation clustering and citation context analysis are combined to concretely define the shared knowledge within a research specialty. The cluster for a large and fast moving biomedical specialty, recombinant-DNA, is presented in terms of the highly cited documents comprising it and their co-citation links. By examining citation contexts in the papers citing the highly cited documents, it is possible to label each of the documents in the cluster with its specific cognitive meaning for the citing authors. Co-citation contexts are used to reveal the relationships among the concepts symbolized by the highly cited documents, providing a cognitive equivalent of the co-citation links. This may open a new way to the investigation of the logic of conceptual change at the specialty level.     

Visualizing the context of citations referencing papers published by Eugene Garfield: a new type of keyword co-occurrence analysis

During Eugene Garfield’s (EG’s) lengthy career as information scientist, he published about 1500 papers. In this study, we use the impressive oeuvre of EG to introduce a new type of bibliometric networks: keyword co-occurrences networks based on the context of citations, which are referenced in a certain paper set (here: the papers published by EG). The citation context is defined by the words which are located around a specific citation. We retrieved the citation context from Microsoft Academic. To interpret and compare the results of the new network type, we generated two further networks: co-occurrence networks which are based on title and abstract keywords from (1) EG’s papers and (2) the papers citing EG’s publications. The comparison of the three networks suggests that papers of EG and citation contexts of papers citing EG are semantically more closely related to each other than to titles and abstracts of papers citing EG. This result accords with the use of citations in research evaluation that is based on the premise that citations reflect the cognitive influence of the cited on the citing publication.     

Patterns of annual citation of highly cited articles and the prediction of their citation ranking: A comparison across subjects

High citation is associated with research quality and consequently findings on highly cited articles are useful to increase understanding of the factors that produce high quality research. This study explores highly cited articles in six subjects, focusing on late citation and peak citation years. Longitudinal citation patterns were found to be highly varied and, on average, different from the remaining articles in each subject. For four of the six subjects, there is a correlation of over 0.42 between the percentage of early citations and total citation ranking but more highly ranked articles had a lower percentage of early citations. Surprisingly, for highly cited articles in all six subjects the prediction of citation ranking of from the sum of citations during their first six years was less accurate than prediction using the sum of the citations for only the fifth and sixth year.     

Characterizing a scientific elite (B): publication and citation patterns of the most highly cited scientists in environmental science and ecology

Science is principally driven by the efforts of a vanishingly small fraction of researchers publishing the majority of scientific research and garnering the majority of citations. Despite this well-established trend, knowledge of exactly how many articles these researchers publish, how highly they are cited, and how they achieved their distinctive accomplishments is meager. This article examines the publication and citation patterns of the world’s most highly cited environmental scientists and ecologists, inquiring into their levels of scientific productivity and visibility, examining relationships between scientific productivity and quality within their research programs, and considering how different publication strategies contribute to these distinctive successes. Generally speaking, highly cited researchers are also highly productive, publishing on average well over 100 articles each. Furthermore, articles published by this group are more highly cited on average than articles published in premier generalist journal like Nature and Science, and their citation to publication ratios are more equitably distributed than is typical. Research specialization and primacy of authorship are important determinants of citation frequency, while geographic differences and collaborative propensity matter less. The article closes with a set of suggestions for those wishing to increase the use of their research by the scientific community.     

Some methodological problems in ranking scientists by citation analysis

A sample of 80 Hungarian scientists, authors or co-authors of a total number of 6273 papers—published between 1930–1976—has been analysed. Citation data to eachpaper were collected form the 1964–76 SCI's by manual search. Citation counts were distinguished with respect to the following categories: (I) the set of cited authors has element(s) common with the set of citing authors (self citation), (II) condition I is not satisfied, but the cited author under study and at least one of the citing authors were co-authors prior to the publication of the cited paper, (III) none of the former criteria is satisfied. The yearly average citation frequency of a paper was not corrected for obsolescence, since there is no evidence that the decay of citation frequency with time is independent of the absolute citedness of the paper. Individual performance has been measured (a) by the sum of the vearly average typeIII fractional citation frequencies over all of the author's papers, (b) by the sum of the yearly average citation frequency normalized to one single-authored paper per year over the period of the author's activity, (c) by the same as ina, but summed up only over the most highly cited papers scattering upwards from the individual's own average, (d) by the fractional authorship, and (e) by the number of items in the author's publication list. The first three parameters seem to be applicable in measuring the utility of the individual's scientific contribution with slightly different emphasis on different aspects. These parameters are uncorrelated with those measuring the output of individuals.     

Renewable energy research 1995–2009: a case study of wind power research in EU, Spain, Germany and Denmark

The paper reports the developments and citation patterns over three time periods of research on Renewable Energy generation and Wind Power 1995–2011 in EU, Spain, Germany and Denmark. Analyses are based on Web of Science and incorporate journal articles as well as conference proceeding papers. Scientometric indicators include publication collaboration ratios, top-player distribution as well as citedness and correspondence analyses of citing publications, relative citation impact, distributions of top-cited as well as top-citing institutions and publication sources and cluster analysis of citing title terms to map knowledge export areas. Findings show an increase in citation impact for Renewable Energy and Wind Power research albeit hampered by scarcely cited conference papers. Although EU maintains its global top position in producing Renewable Energy and Wind Power research the developments of EU and German world shares as well as citation impact are negative during the most recent 7 year period. During the same time the citation impact of Spain and Denmark increase and place both nations among the top-ranking countries in Wind Power research. Spain is the only EU country that increases its world production share from 2000. China is currently ranked three after EU and USA in research output, however with a very low citation impact. Spain, Denmark and Germany each demonstrates distinct collaboration patterns and publication source and citation distribution profiles. More than half the citations to EU Wind Power research are EU-self citations. An expected intensified EU collaboration in the Wind Energy field does not come about. The most productive research institutions in Denmark and Spain are also the most cited ones.     

The nature and relationship between the productivity of journals and their citations in semiconductor literature

The purpose of this study was to investigate the relationship between journals" productivity and their citations in the field of semiconductors. Journal samples were gathered from the INSPEC database, 1978 to 1997 while the data of citation frequency, impact factor, cited half-life and citing half-life were obtained from Science Citation Index, Journal Citation Reports 1997 CD-ROM edition. One thousand and eight hundred and seventy seven journals publishing articles on semiconductors were retrieved. The nature for the data of journal productivity, impact factor, cited half-life and citing half-life are explored. Among these journals, only 672 journals that were covered in JCR were compared. Moreover, statistical tests of more productive journals with cumulative publication in semiconductor >100 were also conducted on the basis of all articles they published annually (for 1997). The results of the study showed that there is a significant correlation between journal productivity and citation frequency and between journal productivity and impact factor. However, there are no associations between journal productivity and cited half-life and between journal productivity and citing half-life. This revised version was published online in August 2006 with corrections to the Cover Date.     

Reception of integrative and complementary medicine (ICM) in scientific journals: a citation and co-word analysis

Even if integrative and complementary medicine (ICM) is a growing scientific field, it is also a highly contested area in terms of scientific legitimacy. The aim of this article is to analyze the reception of ICM research in scientific journals. Is this kind of research acknowledged outside the ICM context, for example, in general or specialized medicine? What is the impact of ICM research? and Is it possible to identify any shift in content, from the original ICM research to the documents where it is acknowledged? The material consisted of two sets: documents published in 12 ICM journals in 2007; and all documents citing these documents during the years 2007–2012. These sets were analyzed with help from citation and co-word analysis. When analyzing the citation pattern, it was clear that a majority of the cited documents were acknowledged in journals and documents that could be related to research areas outside the ICM context, such as pharmacology & pharmacy and plant science—even if the most frequent singular journals and subject categories were connected to ICM. However, after analyzing the content of cited and citing documents, it was striking how similar the content was. It was also evident that much of this research was related to basic preclinical research, in fields such as cell biology, plant pharmacology, and animal experiments.     

The influence of Elfreda Chatman’s theories: a citation context analysis

The range of theoretical frameworks currently being used by researchers into information behaviour is abundant and diverse. We need to examine thoroughly the contribution of theories and models to further research, as this would help to improve future investigations in the field. This paper adopts this approach, by thoroughly examining the influence that Elfreda Chatman’s three middle-range theories have had on subsequent research. A citation context analysis was carried out on the basis of those received by Information poverty theory, life in the round theory and normative behaviour theory. Analysis covered the year of publication, the type of work and the subject-matter of the citing documents. The cites in context or theoretical incidents were analysed for frequency of citation in citing documents, the content of Chatman’s work being cited, the context co-citation analysis, the citation style and the citation location. The analysis of citation in context has allowed us to draw a distinction between the author and her work, while verifying that not all cites are the same. These differences reflect the unequal relevance of these theories to subsequent research.

     

Assessing non-standard article impact using F1000 labels

Faculty of 1000 (F1000) is a post-publishing peer review web site where experts evaluate and rate biomedical publications. F1000 reviewers also assign labels to each paper from a standard list or article types. This research examines the relationship between article types, citation counts and F1000 article factors (FFa). For this purpose, a random sample of F1000 medical articles from the years 2007 and 2008 were studied. In seven out of the nine cases, there were no significant differences between the article types in terms of citation counts and FFa scores. Nevertheless, citation counts and FFa scores were significantly different for two article types: “New finding” and “Changes clinical practice”: FFa scores value the appropriateness of medical research for clinical practice and “New finding” articles are more highly cited. It seems that highlighting key features of medical articles alongside ratings by Faculty members of F1000 could help to reveal the hidden value of some medical papers.     

Journals of general &; internal medicine and surgery: An analysis and comparison of citation

Summary The purpose of this study is to analyze and compare journal citation data, from Journal Citation Reports on the Web 2000, of general and internal medicine and surgery. The source items and five kinds of citation data, i.e. citation counts, impact factor, immediacy index, citing half-life and cited half-life are examined and the correlation between each of the fifteen pairs of citation data is determined based on the Pearson correlation tests. The Fishers Z-transform was employed to test the significant difference between the Pearson correlation coefficient for each pair of citation data of these two subject areas. The following results of this work reveal: the frequently published journals are cited more frequently and also with high impact factor and immediacy index, in addition, they are usually accompanied with short citing half-life (i.e., usually cite current literature). The impact factor and immediacy index has significant correlation with citation counts. A significant correlation also exists between impact factor and immediacy index. However there is no correlation between cited half-life and other citation data, except citing half-life. For journals of general and internal medicine and surgical medicine, there are no significant difference of the Pearson correlation coefficient for the following pair of citation data: source items and citation counts, source items and impact factor, source items and citing half-life, citation counts and citing half-life, impact factor and citing half-life, immediacy index and citing half-life, and cited half-life and citing half-life.     

Evaluating scientific impact of publications: combining citation polarity and purpose

Citation counts are commonly used to evaluate the scientific impact of a publication on the general premise that more citations probably mean more endorsements. However, two questionable assumptions underpin this idea: a) that all authors contributed equally to the paper; and b) that the endorsement is positive. Obviously, neither of these assumptions hold true. Hence, with this study, we examine two components of citations—their purpose, i.e., the reason for the citation, and polarity, being the author’s attitude toward the cited work. Our findings provide a new perspective on the scientific impact of highly-cited publications. Our methodology consists of three steps. Firstly, a pre-trained model composed of a Word2Vec—a well-known word embedding approach—and a convolutional neural network (CNN) is used to identify citation polarity and purpose. Secondly, in a set of highly-cited papers, we compare eight categories of purpose from foundational to critical and three categories of polarity: positive, negative, and neutral. We further explore how different types of papers—those discussing discoveries or those discussing utilitarian topics—influence the evaluation of scientific impact of papers. Finally, we mine and discover the knowledge (e.g. method, concept, tool or data) to explain the actual scientific impact of a highly-cited paper. To demonstrate how combining citation polarity with purpose can provide far greater details of a paper’s scientific impact, we undertake a case study with 370 highly-cited journal articles spanning “Biochemistry & Molecular Biology” and “Genetics & Heredity”. The results yield valuable insights into the assumption about citation counts as a metric for evaluating scientific impact.

     

Can applied science be ‘good science’? Exploring the relationship between patent citations and citation impact in nanoscience

There is a rich literature on how science and technology are related to each other. Patent citation analysis is amongst the most frequently used to tool to track the strengths of links. In this paper we explore the relationship between patent citations and citation impact in nanoscience. Our observations indicate that patent-cited papers perform better in terms of standard bibliometric indicators than comparable publications that are not linked to technology in this way. More specifically, we found that articles cited in patents are more likely to be cited also by other papers. The share of highly cited papers is the most striking result. Instead of the average of 4% of all papers, 13.8% of the papers cited once or twice in patents fall into this category and even 23.5% of the papers more frequently cited in patents receive citation rates far above the standard. Our analyses further demonstrate the presence and the relevance of bandwagon effects driving the development of science and technology.