Search (74 results, page 1 of 4)

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Abstract

The domain of knowledge organization (KO) represents a foundational area of information science. One way to better understand the intellectual structure of the KO domain is to apply bibliometric methods to key contributors to the literature. This study analyzes the most prolific contributing authors to the journal Knowledge Organization, the sources they cite and the citations they receive for the period 1993 to 2016. The analyses were conducted using visualization outcomes of citation, co-citation and author bibliographic coupling analysis to reveal theoretical points of reference among authors and the most prominent research themes that constitute this scientific community. Birger Hjørland was the most cited author, and was situated at or near the middle of each of the maps based on different citation relationships. The proximities between authors resulting from the different citation relationships demonstrate how authors situate themselves intellectually through the citations they give and how other authors situate them through the citations received. There is a consistent core of theoretical references as well among the most productive authors. We observed a close network of scholarly communication between the authors cited in this core, which indicates the actual role of the journal Knowledge Organization as a space for knowledge construction in the area of knowledge organization.

Source

Knowledge organization. 45(2018) no.1, S.13-22

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Abstract

Patent analysis has become important for management as it offers timely and valuable information to evaluate R&D performance and identify the prospects of patents. This study explores the scattering patterns of patent impact based on citations in 3 distinct technological areas, the liquid crystal, semiconductor, and drug technological areas, to identify the core patents in each area. The research follows the approach from Bradford's law, which equally divides total citations into 3 zones. While the result suggests that the scattering of patent citations corresponded with features of Bradford's law, the proportion of patents in the 3 zones did not match the proportion as proposed by the law. As a result, the study shows that the distributions of citations in all 3 areas were more concentrated than what Bradford's law proposed. The Groos (1967) droop was also presented by the scattering of patent citations, and the growth rate of cumulative citation decreased in the third zone.

Date

22. 8.2014 17:11:29

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Abstract

Purpose - The purpose of this paper is to analyse the global scientific outputs of ontology research, an important emerging discipline that has huge potential to improve information understanding, organization, and management. Design/methodology/approach - This study collected literature published during 1900-2012 from the Web of Science database. The bibliometric analysis was performed from authorial, institutional, national, spatiotemporal, and topical aspects. Basic statistical analysis, visualization of geographic distribution, co-word analysis, and a new index were applied to the selected data. Findings - Characteristics of publication outputs suggested that ontology research has entered into the soaring stage, along with increased participation and collaboration. The authors identified the leading authors, institutions, nations, and articles in ontology research. Authors were more from North America, Europe, and East Asia. The USA took the lead, while China grew fastest. Four major categories of frequently used keywords were identified: applications in Semantic Web, applications in bioinformatics, philosophy theories, and common supporting technology. Semantic Web research played a core role, and gene ontology study was well-developed. The study focus of ontology has shifted from philosophy to information science. Originality/value - This is the first study to quantify global research patterns and trends in ontology, which might provide a potential guide for the future research. The new index provides an alternative way to evaluate the multidisciplinary influence of researchers.

Date

20. 1.2015 18:30:22
17. 9.2018 18:22:23

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Abstract

Purpose The purpose of this paper is to analyse the author self-citation behavior in the field of Library and Information Science. Various factors governing the author self-citation behavior have also been studied. Design/methodology/approach The 2012 edition of Social Science Citation Index was consulted for the selection of LIS journals. Under the subject heading "Information Science and Library Science" there were 84 journals and out of these 12 journals were selected for the study based on systematic sampling. The study was confined to original research and review articles that were published in select journals in the year 2009. The main reason to choose 2009 was to get at least five years (2009-2013) citation data from Web of Science Core Collection (excluding Book Citation Index) and SciELO Citation Index. A citation was treated as self-citation whenever one of the authors of citing and cited paper was common, i.e., the set of co-authors of the citing paper and that of the cited one are not disjoint. To minimize the risk of homonyms, spelling variances and misspelling in authors' names, the authors compared full author names in citing and cited articles. Findings A positive correlation between number of authors and total number of citations exists with no correlation between number of authors and number/share of self-citations, i.e., self-citations are not affected by the number of co-authors in a paper. Articles which are produced in collaboration attract more self-citations than articles produced by only one author. There is no statistically significant variation in citations counts (total and self-citations) in works that are result of different types of collaboration. A strong and statistically significant positive correlation exists between total citation count and frequency of self-citations. No relation could be ascertained between total citation count and proportion of self-citations. Authors tend to cite more of their recent works than the work of other authors. Total citation count and number of self-citations are positively correlated with the impact factor of source publication and correlation coefficient for total citations is much higher than that for self-citations. A negative correlation exhibits between impact factor and the share of self-citations. Of particular note is that the correlation in all the cases is of weak nature. Research limitations/implications The research provides an understanding of the author self-citations in the field of LIS. readers are encouraged to further the study by taking into account large sample, tracing citations also from Book Citation Index (WoS) and comparing results with other allied subjects so as to validate the robustness of the findings of this study. Originality/value Readers are encouraged to further the study by taking into account large sample, tracing citations also from Book Citation Index (WoS) and comparing results with other allied subjects so as to validate the robustness of the findings of this study.

Date

20. 1.2015 18:30:22

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Abstract

Applying a recently developed method for measuring the level of specialization over time for a selection of library and information science (LIS)-core journals seems to reveal that Journal of the Association for Information Science and Technology (JASIST) is slowly transforming into a specialty journal. The transformation seems to originate from a growing interest in bibliometric topics. This is evident from a longitudinal study (1990-2012) of the bibliometric coupling strength between Scientometrics and other LIS-core journals (including JASIST). The cause of this gradual transformation is discussed, and possible explanations are analyzed.

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Abstract

The diversity of bibliometric indices today poses the challenge of exploiting the relationships among them. Our research uncovers the best core set of relevant indices for predicting other bibliometric indices. An added difficulty is to select the role of each variable, that is, which bibliometric indices are predictive variables and which are response variables. This results in a novel multioutput regression problem where the role of each variable (predictor or response) is unknown beforehand. We use Gaussian Bayesian networks to solve the this problem and discover multivariate relationships among bibliometric indices. These networks are learnt by a genetic algorithm that looks for the optimal models that best predict bibliometric data. Results show that the optimal induced Gaussian Bayesian networks corroborate previous relationships between several indices, but also suggest new, previously unreported interactions. An extended analysis of the best model illustrates that a set of 12 bibliometric indices can be accurately predicted using only a smaller predictive core subset composed of citations, g-index, q2-index, and hr-index. This research is performed using bibliometric data on Spanish full professors associated with the computer science area.

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Abstract

The publication performance of 30 scientometricians is studied. The individuals are classified into 3 cohorts according to their manifested professional recognition, as Price medalists (Pm), members of the editorial board of Scientometrics and the Journal of Informetrics (Rw), and session chairs (Sc) at an International Society of Scientometrics and Informetrics (ISSI) conference. Several core impact indicators are calculated: h, g, p, citation distribution score (CDS), percentage rank position (PRP), and weight of influence of papers (WIP10). The indices significantly correlate with each other. The mean value of the indices of the cohorts decreases parallel with the decrease in professional recognition: Pm?>?Rw?>?Sc. The 30 scientometricians studied were clustered according to the core impact indices. The members in the clusters so obtained overlap only partly with the members in the cohorts made by professional recognition. The Total Overlap is calculated by dividing the sum of the diagonal elements in the cohorts-clusters matrix with the total number of elements, times 100. The highest overlap (76.6%) was obtained with the g-index. Accordingly, the g-index seems to have the greatest discriminative power in the system studied. The cohorts-clusters method may be used for validating scientometric indicators.

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Abstract

This paper introduces a keyword map of the labels used by the scientists registered in the Google Scholar Citations (GSC) database from December 2011. In all, 15,000 random queries were formulated to GSC to obtain a list of 26,682 registered users. From this list a network graph of 6,660 labels was built and classified according to the Scopus Subject Area classes. Results display a detailed label map of the most used (>15 times) tags. The structural analysis shows that the core of the network is occupied by computer science-related disciplines that account for the most used and shared labels. This core is surrounded by clusters of disciplines related or close to computing such as Information Sciences, Mathematics, or Bioinformatics. Classical areas such as Chemistry and Physics are marginalized in the graph. It is suggested that GSC would in the future be an accurate source to map Science because it is based on the labels that scientists themselves use to describe their own research activity.

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Abstract

Most measures of networks are based on the nodes, although links are also elementary units in networks and represent interesting social or physical connections. In this work we suggest an option for exploring networks, called the h-strength, with explicit focus on links and their strengths. The h-strength and its extensions can naturally simplify a complex network to a small and concise subnetwork (h-subnet) but retains the most important links with its core structure. Its applications in 2 typical information networks, the paper cocitation network of a topic (the h-index) and 5 scientific collaboration networks in the field of "water resources," suggest that h-strength and its extensions could be a useful choice for abstracting, simplifying, and visualizing a complex network. Moreover, we observe that the 2 informetric models, the Glänzel-Schubert model and the Hirsch model, roughly hold in the context of the h-strength for the collaboration networks.

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Abstract

The h-index provides us with 9 natural classes which can be written as a matrix of 3 vectors. The 3 vectors are: X = (X1, X2, X3) and indicates publication distribution in the h-core, the h-tail, and the uncited ones, respectively; Y = (Y1, Y2, Y3) denotes the citation distribution of the h-core, the h-tail and the so-called "excess" citations (above the h-threshold), respectively; and Z = (Z1, Z2, Z3) = (Y1-X1, Y2-X2, Y3-X3). The matrix V = (X,Y,Z)T constructs a measure of academic performance, in which the 9 numbers can all be provided with meanings in different dimensions. The "academic trace" tr(V) of this matrix follows naturally, and contributes a unique indicator for total academic achievements by summarizing and weighting the accumulation of publications and citations. This measure can also be used to combine the advantages of the h-index and the integrated impact indicator (I3) into a single number with a meaningful interpretation of the values. We illustrate the use of tr(V) for the cases of 2 journal sets, 2 universities, and ourselves as 2 individual authors.

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Abstract

This article first analyzes library and information science (LIS) research articles published in core LIS journals in 2005. It also examines the development of LIS from 1965 to 2005 in light of comparable data sets for 1965, 1985, and 2005. In both cases, the authors report (a) how the research articles are distributed by topic and (b) what approaches, research strategies, and methods were applied in the articles. In 2005, the largest research areas in LIS by this measure were information storage and retrieval, scientific communication, library and information-service activities, and information seeking. The same research areas constituted the quantitative core of LIS in the previous years since 1965. Information retrieval has been the most popular area of research over the years. The proportion of research on library and information-service activities decreased after 1985, but the popularity of information seeking and of scientific communication grew during the period studied. The viewpoint of research has shifted from library and information organizations to end users and development of systems for the latter. The proportion of empirical research strategies was high and rose over time, with the survey method being the single most important method. However, attention to evaluation and experiments increased considerably after 1985. Conceptual research strategies and system analysis, description, and design were quite popular, but declining. The most significant changes from 1965 to 2005 are the decreasing interest in library and information-service activities and the growth of research into information seeking and scientific communication.

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Abstract

How does publication pressure in modern-day universities affect the intrinsic and extrinsic rewards in science? By using a worldwide survey among demographers in developed and developing countries, the authors show that the large majority perceive the publication pressure as high, but more so in Anglo-Saxon countries and to a lesser extent in Western Europe. However, scholars see both the pros (upward mobility) and cons (excessive publication and uncitedness, neglect of policy issues, etc.) of the so-called publish-or-perish culture. By measuring behavior in terms of reading and publishing, and perceived extrinsic rewards and stated intrinsic rewards of practicing science, it turns out that publication pressure negatively affects the orientation of demographers towards policy and knowledge sharing. There are no signs that the pressure affects reading and publishing outside the core discipline.

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Abstract

Of h-type indices available now, the g-index is an important one in that it not only keeps some advantages of the h-index but also counts citations from highly cited articles. However, the g-index has a drawback that one has to add fictitious articles with zero citation to calculate this index in some important cases. Based on an alternative definition without introducing fictitious articles, an analytical method has been proposed to calculate the g-index based approximately on the h-index and the e-index. If citations for a scientist are ranked by a power law, it is shown that the g-index can be calculated accurately by the h-index, the e-index, and the power parameter. The relationship of the h-, g-, and e-indices presented here shows that the g-index contains the citation information from the h-index, the e-index, and some papers beyond the h-core.

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Abstract

International collaboration is being heralded as the hallmark of contemporary scientific production. Yet little quantitative evidence has portrayed the landscape and trends of such collaboration. To this end, 14,000,000 documents indexed in Thomson Reuters's Web of Science (WoS) were studied to provide a state-of-the-art description of scientific collaborations across the world. The results indicate that the number of authors in the largest research teams have not significantly grown during the past decade; however, the number of smaller research teams has seen significant increases in growth. In terms of composition, the largest teams have become more diverse than the latter teams and tend more toward interinstitutional and international collaboration. Investigating the size of teams showed large variation between fields. Mapping scientific cooperation at the country level reveals that Western countries situated at the core of the map are extensively cooperating with each other. High-impact institutions are significantly more collaborative than others. This work should inform policy makers, administrators, and those interested in the progression of scientific collaboration.

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Abstract

Using the library and information science journals 2003-2012 in Nanjing University's Chinese Social Sciences Citation Index as data sources, the paper reveals the citation structure implied in these journals by applying social network analysis. Results show that, first, journal knowledge transfer activity in library and information science is frequent, and both the level of knowledge and discipline integration as well as the knowledge gap influenced knowledge transfer activity. According to the out-degree and in-degree, journals can be divided into three kinds. Second, based on professional bias and citation frequency, the knowledge transfer network can be divided into four blocks. With the change of discipline capacity and knowledge gap among journals, the "core-periphery" structure of the knowledge transfer network is getting weaker. Finally, regions of the knowledge transfer network evolved from a "weak-weak" subgroup to a "strong-weak" subgroup or a "weak-strong" subgroup, and then move to a "strong-strong" subgroup.

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Abstract

This study is concerned with differences in referencing patterns between book literature and periodical publications. Four indicators, the mean reference rate per page, the percentage of references to Web of Science journal literature, the mean reference age, and Price Index, were applied to analyze the reference patterns of three publication types: books, book chapter articles and journal articles. References of publications indexed in Web of Science Core Collection were analyzed for two periods (2005-2009, 2010-2013) and across 15 disciplines. Journal article authors cite more recent references and more references from serial publications than monograph authors. The difference between the sciences and the SSH is as obvious as the difference between periodical and non-serial publications. However, the reference patterns of social sciences are much more similar to science fields than humanities, especially for monographs. The subject characteristics of reference pattern are strongly affected by publication types. Furthermore, journal publications have stronger associations between ageing indicators and the share of WoS journal references than monographs.

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Date

18. 3.2014 19:13:22

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Abstract

This work identifies changes in dominant topics in library and information science (LIS) over time, by analyzing the 3,121 doctoral dissertations completed between 1930 and 2009 at North American Library and Information Science programs. The authors utilize latent Dirichlet allocation (LDA) to identify latent topics diachronically and to identify representative dissertations of those topics. The findings indicate that the main topics in LIS have changed substantially from those in the initial period (1930-1969) to the present (2000-2009). However, some themes occurred in multiple periods, representing core areas of the field: library history occurred in the first two periods; citation analysis in the second and third periods; and information-seeking behavior in the fourth and last period. Two topics occurred in three of the five periods: information retrieval and information use. One of the notable changes in the topics was the diminishing use of the word library (and related terms). This has implications for the provision of doctoral education in LIS. This work is compared to other earlier analyses and provides validation for the use of LDA in topic analysis of a discipline.

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Abstract

It was argued recently that the g-index is a measure of a researcher's specific impact (i.e., impact per paper) as much as it is a measure of overall impact. While this is true for the productive "core" of publications, it can be argued that the g-index does not differ from the square root of the total number of citations in a bibliometrically meaningful way when the entire publication list is considered. The R-index also has a tendency to follow total impact, leaving only the A-index as a true measure of specific impact. The main difference between the g-index and the h-index is that the former penalizes consistency of impact whereas the latter rewards such consistency. It is concluded that the h-index is a better bibliometric tool than is the g-index, and that the square root of the total number of citations is a convenient measure of a researcher's overall impact.

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Abstract

In many scientific fields, the order of coauthors on a paper conveys information about each individual's contribution to a piece of joint work. We argue that in prior network analyses of coauthorship networks, the information on ordering has been insufficiently considered because ties between authors are typically symmetrized. This is basically the same as assuming that each coauthor has contributed equally to a paper. We introduce a solution to this problem by adopting a coauthorship credit allocation model proposed by Kim and Diesner (2014), which in its core conceptualizes coauthoring as a directed, weighted, and self-looped network. We test and validate our application of the adopted framework based on a sample data of 861 authors who have published in the journal Psychometrika. The results suggest that this novel sociometric approach can complement traditional measures based on undirected networks and expand insights into coauthoring patterns such as the hierarchy of collaboration among scholars. As another form of validation, we also show how our approach accurately detects prominent scholars in the Psychometric Society affiliated with the journal.