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.     

A bibliometric analysis of plagiarism and self-plagiarism through Déjà vu

Plagiarism is one of the most important current debates among scientific stakeholders. A separate but related issue is the use of authors’ own ideas in different papers (i.e., self-plagiarism). Opinions on this issue are mixed, and there is a lack of consensus. Our goal was to gain deeper insight into plagiarism and self-plagiarism through a citation analysis of documents involved in these situations. The Déjà vu database, which comprises around 80,000 duplicate records, was used to select 247 pairs of documents that had been examined by curators on a full text basis following a stringent protocol. We then used the Scopus database to perform a citation analysis of the selected documents. For each document pair, we used specific bibliometric indicators, such as the number of authors, full text similarity, journal impact factor, the Eigenfactor, and article influence. Our results confirm that cases of plagiarism are published in journals with lower visibility and thus tend to receive fewer citations. Moreover, full text similarity was significantly higher in cases of plagiarism than in cases of self-plagiarism. Among pairs of documents with shared authors, duplicates not citing the original document showed higher full text similarity than those citing the original document, and also showed greater overlap in the references cited in the two documents.     

Reference standards for citation based assessments

One of the most crucial points of citation-based assessments is to find proper reference standards to which the otherwise meaningless plain citation counts can be compared. Using such standards, mere absolute numbers can be turned into relative indicators, suitable for cross-national and cross-field comparisons. In the present study, three possible choice of reference standards for citation assessments are discussed. Citation rates of publications under study can be compared to the average citation rates of the papers of the publishing journals to result inRelative Citation Rate (RCR), an indicator successfully used in several comparative scientometric analyses (see, e.g. Refs 1–5). A more customized reference set is defined by therelated records in the new CD Edition of theScience Citation Index database. Using the socalled bibliographic coupling technique, a set of papers with a high measure of similarity in their list of references is assigned to every single paper of the database. Beside of being an excellent retrieval tool, related records provide a suitable reference set to assess the relative standing of a given set of papers as measured by citation indicators. The third choice introduced in this study is specifically designed for assessing journals. For this purpose, the set of journals cited by the journal in question seems to be a useful basis to compare with. The pros and cons of the three choices are discussed and several examples are given.     

Citation analysis of Ted Nelson’s works and his influence on hypertext concept

This study investigates Ted Nelson’s works and the influence of his hypertext concept through citation analysis, including citation counting, characteristics of citing articles on language, document type, citing year, discipline, and citation content. The selection of the Nelson’s works was based on searching Library Literature & Information Science, Library and Information Science Abstracts, Google and Yahoo search engines. The citation data were compiled from the database of Web of Science. The results of the study reveal that hypertext has directly great impact on information retrieval and world wide web; therefore, the concept has had profound influence on information, library and computer science disciplines. Moreover, the influence of Nelson’s works spreads to other disciplines variously, especially on education, literature, business and economics, engineering, sociology, psychology, etc. The citation context analysis of citing articles on information and library science reveals that (1) definition, orientation and general introduction of hypertext; (2) relation of Vannevar Bush and Ted Nelson in terms of hypertext; (3) Nelson’s Xanadu system and its component of hypertext; (4) the application of hypertext in information science and library science are four most citing purpose.     

Investigating the integrated landscape of the intellectual topology of bioinformatics

We aim at identifying (1) whether and how various data sources influence mapping an intellectual structure of the field of bioinformatics, and (2) the landscape of bioinformatics by integrating those sources. To this end, we conduct a comprehensive bibliometric analysis by harvesting bibliographic information from DBLP, PubMed Central, and Web of Science. We then measure and compare topological characteristics of networks generated using these sources. The results show a dichotomous pattern dominated by PubMed Central and WoS. In addition, a few influential scientists in the field of bioinformatics receive very high citations from their colleagues, which is a driving force to bloom the field. These few scientists are connected to a much larger research community. Most of the researchers are intellectually linked within a few steps, in spite of the domain’s interdisciplinary characteristics. Particularly, influential authors consist of a small world. We also identify that there is not a coherent body of discipline in bioinformatics since the field is still under development. Finally, the journals and conferences indexed by each source cover different research topics, and PubMed Central is more inclusive than DBLP as an indexing database.     

Using neural-network based paragraph embeddings for the calculation of within and between document similarities

Science mapping using document networks comes often with the implicit assumption that scientific papers are indivisible units with unique links to neighbour documents. Research on proximity in co-citation analysis and the study of lexical properties of sections and citation contexts indicate that this assumption doesn’t always hold. Moreover, the meaning of words and co-words depends on the context in which they appear. This study proposes the use of a neural network architecture for word and paragraph embeddings (Doc2Vec) for the measurement of similarity among those smaller units of analysis. It is shown that paragraphs in the “Introduction” and the “Discussion” Section are more similar to the abstract, that the similarity among paragraphs is related to -but not linearly- the distance between the paragraphs. The “Methodology” Section is least similar to the other sections. Abstracts of citing-cited documents are more similar than random pairs and the context in which a reference appears is most similar to the abstract of the cited document. This novel approach with higher granularity can be used for bibliometric aided retrieval and to assist in measuring interdisciplinarity through the application of network-based centrality measures.

     

Citation context analysis and aging patterns of journal articles in molecular genetics

To compare citation history and contextual importance, eleven highly cited articles, 4 slowly aging (Type 1) and 7 quickly aging (Type 2), were ranked using an aggregate citation context measure, the Mean Utility Index. Based on citations in late (PY 6 & 7) source articles, methods papers consistently ranked higher than papers cited for research results and theoretical implications, and Type 1 methods papers ranked above all Type 2 papers. A Type 1 paper representing an important theoretical concept could not be distinguished from Type 2 papers using citation context alone.     

A relevance ranking method for citation-based search results

A growing number of researchers are exploring the use of citation relationships such as direct citation, bibliographic coupling, and co-citation for information retrieval in scientific databases and digital libraries. In this paper, I propose a method of ranking the relevance of citation-based search results to a set of key, or seed, papers by measuring the number of citation relationships they share with those key papers. I tested the method against 23 published systematic reviews and found that the method retrieved 87% of the studies included in these reviews. The relevance ranking approach identified a subset of the citation search results that comprised 27% of the total documents retrieved by the method, and 7% of the documents retrieved by these reviews, but that contained 75% of the studies included in these reviews. Additional testing suggested that the method may be less appropriate for reviews that combine literature in ways that are not reflected in the literature itself. These results suggest that this ranking method could be useful in a range of information retrieval contexts.     

The representative works of scientists

Nowadays identifying the personal representative works is becoming increasingly important and necessary for scientists in many cases, such as faculty hiring and promotion applications. There are already a few methods based on different criteria for selecting the representative works of a scientist, like citation count. In addition, we can observe that some researchers always produce many similar quality scientific papers and some researchers have several highly cited papers compared with his or her other papers. In this context, we propose to use the maximum gap in a histogram of a scientist’s sorted papers’ citation counts to classify his or her papers into two groups, i.e. representative papers and regular papers. Based on the maximum gap, we then design an indicator \(D_{r}\) to quantify the impact difference between scientist’s representative works and regular works. We apply this selection method and \(D_{r}\) index into the data of American Physical Society (APS) journals. The results indicate that the selection method can better identify the representative works of Nobel laureates in Physics compared with using the most cited paper. We also find that the number of representative works selected by our method is related to \(D_{r}\). A larger number of selected papers would appear when the value of \(D_{r}\) index is relatively smaller. Meanwhile, we also observe that \(D_{r}\) is weakly correlated with the h index and total citation.     

Approximating total citation counts from first author counts and from total papers

This paper is an attempt to improve on the approximation. First author citations (C_f)≈Total citations (C_t) of an author's publications without the work of making the complete citation count under the author and all co-author names. Using the bibliographies of all faculty from each of four large departments: Physics, Chemistry, Materials Sciences, and Biosciences, in the same university, both first author and complete citation counts were made, care being taken to avoid the most common errors in such counts. It is shown that the function C_f·T/F (where T and F are the total number of papers and F those with subject author's name first) correlates strongly (>90%) with C_t. We find also that C_t correlates strongly with T. The data also may be used as one more line of evidence to obtain normalizing ratios for possible comparisons of productivityacross different disciplinary universes. A very tentative ratio from different studies would be 8 (Chem.)=4 (Physics)=2.5 (Mat. Sci.)=2 (Mathematics)=4.5 (Biophysics-Biochemistry).     

The use of citation speed to understand the effects of a multi-institutional science center

The extent to which an article attracts citations has long been of interest. However, recent research has emphasized not just the receipt but also the pacing of citation. Citation speed has been shown to be affected by journal prestige and self-citation but also public funding of research. Amidst these viewpoints, this paper explores the speed of article citation of a multi-institutional, multi-disciplinary publicly funded research center relative to that of a comparison group of articles. Results indicate that articles by authors affiliated with the center are significantly more likely to have early-cited papers within the year of publication than the random comparison group, with controls by field also being significant. Implications for the ability of a publicly funded center to attract attention toward articles are discussed.     

The “meaning” of citation in the context of a scientifically peripheral country

This paper reports an investigation into the referencing pattern of Brazilian agricultural scientists. The study was based on the use of both quantitative data-citations appearing in a sizeable sample of articles published by these scientists—and qualitative data-interviews with a large number of scientists who authored the source, papers. The aim was to explore the extent to which citation counts may be taken as valid indicators of the quality, influence or impact of published scientific knowledge in the general context of a scientifically peripheral country. The findings presented confirm the view that in this context, citation patterns are significantly influenced by factors external to the scientific realm and, thus, reflect neither simply the quality, influence nor even the impact of the research work referred to.     

To include or not: the role of review papers in citation-based analysis

Citation information helps researchers observe the evolution of the knowledge. In scientific publications, a review paper discusses a professional field and thus tends to have more citations than general papers do. This study investigated whether specific characteristics of review papers induce different results in citation-based analysis. From the Scopus database, we collected scientific publications in a specific research field, e-tourism, to examine the role of review papers in citation-based analysis. The dataset includes 1421 publications covering the period from the 1988–2015. Empirical statistics show that review papers’ specific citation patterns influence citation analysis. First, in the main path analysis, the result expresses review papers’ integrative role in linking papers from diverse perspectives toward a clear mainstream topic. Second, in a well-defined research context, review papers introduce bias in citation-based clustering analysis because the specific high citation pattern in review papers obfuscates the grouping process. When using citation information in analysis, scholars must consider the purpose of the study and treat review papers distinctly to avoid bias when using certain analysis methods and datasets.     

Patents in nanotechnology: an analysis using macro-indicators and forecasting curves

In this study, we evaluated future trends of worldwide patenting in nanotechnology and its domains using logistic growth curves while the patent activity from the main countries, technological domains and subdomains were assessed in four different contexts: worldwide, patents filed in the United States Patent and Trademark Office (USPTO), and patents applications in the triadic (TRIAD) and in the tetradic (TETRAD) countries. The indicators were developed based on a set of records recovered from the Derwent Innovation Index database. Nanotechnology has recently emerged as a new research field, with logistic trend behaviors generating interesting discussions since they suggest that technological development in nanotechnology and its domains has reached an initial maturation stage. Future scenarios were compiled due to the difficult to establish upper limits to forecasting curves. Although China’s share of patents is small in some cases, it was the only country to constantly increase the number of patents from a worldwide perspective. In contrast, the USA and the EU were the most active in the USPTO, TRIAD and TETRAD cases, followed by Japan and Korea. The technological subdomains of main interest from countries/region changed according to the perspective adopted, even though there was a clear bias towards semiconductors, surface treatments, electrical components, macromolecular chemistry, materials–metallurgy, pharmacy–cosmetics and analysis–measurement–control subdomains. We conclude that monitoring nanotechnology advances should be constantly reviewed in order to confirm the evidence observed and forecasted.     

CAD: an algorithm for citation-anchors detection in research papers

Citations are very important parameters and are used to take many important decisions like ranking of researchers, institutions, countries, and to measure the relationship between research papers. All of these require accurate counting of citations and their occurrence (in-text citation counts) within the citing papers. Citation anchors refer to the citation made within the full text of the citing paper for example: ‘[1]’, ‘(Afzal et al, 2015)’, ‘[Afzal, 2015]’ etc. Identification of citation-anchors from the plain-text is a very challenging task due to the various styles and formats of citations. Recently, Shahid et al. highlighted some of the problems such as commonality in content, wrong allotment, mathematical ambiguities, and string variations etc in automatically identifying the in-text citation frequencies. The paper proposes an algorithm, CAD, for identification of citation-anchors and its in-text citation frequency based on different rules. For a comprehensive analysis, the dataset of research papers is prepared: on both Journal of Universal Computer Science (J.UCS) and (2) CiteSeer digital libraries. In experimental study, we conducted two experiments. In the first experiment, the proposed approach is compared with state-of-the-art technique over both datasets. The J.UCS dataset consists of 1200 research papers with 16,000 citation strings or references while the CiteSeer dataset consists of 52 research papers with 1850 references. The total dataset size becomes 1252 citing documents and 17,850 references. The experiments showed that CAD algorithm improved F-score by 44% and 37% respectively on both J.UCS and CiteSeer dataset over the contemporary technique (Shahid et al. in Int J Arab Inf Technol 12:481–488, 2014). The average score is 41% on both datasets. In the second experiment, the proposed approach is further analyzed against the existing state-of-the-art tools: CERMINE and GROBID. According to our results, the proposed approach is best performing with F1 of 0.99, followed by GROBID (F1 0.89) and CERMINE (F1 0.82).     

Condensed matter physics journals

On the basis of a citation/reference criterion, 20 core journals are selected in the field of condensed matter physics. Citation data and indicators from 1980Journal Citation Reports reveal their different characteristic features such as applied orientation, communication function and longevity. The manually obtained data for the core journals are written into a matrix in order to determine an appropriate ranking parameter. The method ofPrice is used first to reduce the diagonal elements and then, following the method ofGeller, influence weights are calculated for the core journals. Influence weights are determined also for non-core journals using only the references received from the core.     

R&D dynamics and scientific breakthroughs in HIV/AIDS drugs development: the case of Integrase Inhibitors

Transformations and applications of scientific knowledge into new technologies are usually complex interactive processes. Is it possible to detect, from bibliographic information alone, structural alterations and significant events within these processes that may indicate breakthrough discoveries? In this empirical study we focus on R&D processes leading to HIV/AIDS medicines called Integrase Inhibitors. Where scientific progress and discoveries are reflected in research papers, patents signify inventions and technological achievements. Our temporal analysis of distinctive events in this R&D area, tracing trends within both bibliographic information sources, is driven by three bibliometric indicators: (1) contributions of ‘bridging researchers’ who are also inventors, (2) ‘key papers’ that subject experts in the field considered milestones in the research process, and (3) the multidisciplinary impact of those papers. The main results indicate that a combination of key papers, bridging researchers and multidisciplinary impact might help track potential ‘Charge type’ breakthrough developments.