Search (83 results, page 2 of 5)

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Abstract

Ahlgren, Jarneving, and. Rousseau review accepted procedures for author co-citation analysis first pointing out that since in the raw data matrix the row and column values are identical i,e, the co-citation count of two authors, there is no clear choice for diagonal values. They suggest the number of times an author has been co-cited with himself excluding self citation rather than the common treatment as zeros or as missing values. When the matrix is converted to a similarity matrix the normal procedure is to create a matrix of Pearson's r coefficients between data vectors. Ranking by r and by co-citation frequency and by intuition can easily yield three different orders. It would seem necessary that the adding of zeros to the matrix will not affect the value or the relative order of similarity measures but it is shown that this is not the case with Pearson's r. Using 913 bibliographic descriptions form the Web of Science of articles form JASIS and Scientometrics, authors names were extracted, edited and 12 information retrieval authors and 12 bibliometric authors each from the top 100 most cited were selected. Co-citation and r value (diagonal elements treated as missing) matrices were constructed, and then reconstructed in expanded form. Adding zeros can both change the r value and the ordering of the authors based upon that value. A chi-squared distance measure would not violate these requirements, nor would the cosine coefficient. It is also argued that co-citation data is ordinal data since there is no assurance of an absolute zero number of co-citations, and thus Pearson is not appropriate. The number of ties in co-citation data make the use of the Spearman rank order coefficient problematic.

Date

9. 7.2006 10:22:35

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Abstract

The debate about which similarity measure one should use for the normalization in the case of Author Co-citation Analysis (ACA) is further complicated when one distinguishes between the symmetrical co-citation - or, more generally, co-occurrence - matrix and the underlying asymmetrical citation - occurrence - matrix. In the Web environment, the approach of retrieving original citation data is often not feasible. In that case, one should use the Jaccard index, but preferentially after adding the number of total citations (i.e., occurrences) on the main diagonal. Unlike Salton's cosine and the Pearson correlation, the Jaccard index abstracts from the shape of the distributions and focuses only on the intersection and the sum of the two sets. Since the correlations in the co-occurrence matrix may be spurious, this property of the Jaccard index can be considered as an advantage in this case.

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Abstract

Citation analysis of documents retrieved from the Medline database (at the Web of Knowledge) has been possible only on a case-by-case basis. A technique is presented here for citation analysis in batch mode using both Medical Subject Headings (MeSH) at the Web of Knowledge and the Science Citation Index at the Web of Science (WoS). This freeware routine is applied to the case of "Brugada Syndrome," a specific disease and field of research (since 1992). The journals containing these publications, for example, are attributed to WoS categories other than "cardiac and cardiovascular systems", perhaps because of the possibility of genetic testing for this syndrome in the clinic. With this routine, all the instruments available for citation analysis can now be used on the basis of MeSH terms. Other options for crossing between Medline, WoS, and Scopus are also reviewed.

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Abstract

Using the Scopus dataset (1996-2007) a grand matrix of aggregated journal-journal citations was constructed. This matrix can be compared in terms of the network structures with the matrix contained in the Journal Citation Reports (JCR) of the Institute of Scientific Information (ISI). Because the Scopus database contains a larger number of journals and covers the humanities, one would expect richer maps. However, the matrix is in this case sparser than in the case of the ISI data. This is because of (a) the larger number of journals covered by Scopus and (b) the historical record of citations older than 10 years contained in the ISI database. When the data is highly structured, as in the case of large journals, the maps are comparable, although one may have to vary a threshold (because of the differences in densities). In the case of interdisciplinary journals and journals in the social sciences and humanities, the new database does not add a lot to what is possible with the ISI databases.

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Abstract

Four cases, illustrated by four examples, of duplicate or highly related publications can be distinguished and are analyzed here using citation data obtained from the Science Citation Index (SCI): (1) publication by different authors in the same journal; (2) the same author(s) publishing in different journals; (3) publication by different authors in different journals; (4) the same author(s) publishing highly related papers simultaneously in the same journal, often as part of a series of papers. Example 1, illustrating case 1, is an occurrence of highly related publications in mechanistic organic chemistry. Example 2, from analytical organic chemistry, contains elements of cases 2 and 3. Example 3, dealing solely with case 3, discusses two time-delayed publications from analytical biochemistry, which were highlighted by Garfield several times in the past to show how the SCI could be utilized to avoid duplicate publication. Example 4, derived from synthetic organic chemistry (total syntheses of taxol), contains elements of cases 1, 3, and 4 and, to a lesser extent, case 2. The citation records of the highly related or duplicate publications can deviate considerably from the journal impact factors; this was observed in three of the four examples relating to cases 2, 3, and 4. The examples suggest that citation of a paper may depend significantly on the journal in which it is published. As an indicator of this dependence, the journals in which the papers used in the present examples appeared were examined. Other factors such as key words in the paper title may also play a role.

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Abstract

This article provides an overview of studies that have used citation analysis in the field of humanities in the period 1951 to 2010. The work is based on an exhaustive search in databases-particularly those in library and information science-and on citation chaining from papers on citation analysis. The results confirm that use of this technique in the humanities is limited, and although there was some growth in the 1970s and 1980s, it has stagnated in the past 2 decades. Most of the work has been done by research staff, but almost one third involves library staff, and 15% has been done by students. The study also showed that less than one fourth of the works used a citation database such as the Arts & Humanities Citation Index and that 21% of the works were in publications other than library and information science journals. The United States has the greatest output, and English is by far the most frequently used language, and 13.9% of the studies are in other languages.

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Abstract

This article studies citation practices in the arts and humanities from a theoretical and conceptual viewpoint, drawing on studies from fields like linguistics, history, library & information science, and the sociology of science. The use of references in the humanities is discussed in connection with the growing interest in the possibilities of applying citation analysis to humanistic disciplines. The study shows how the use of references within the humanities is connected to concepts of originality, to intellectual organization, and to searching and writing. Finally, it is acknowledged that the use of references is connected to stylistic, epistemological, and organizational differences, and these differences must be taken into account when applying citation analysis to humanistic disciplines.

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Abstract

A new approach for investigating the correlation between research quality and citation counts is presented and applied to a case study of the relationship between peer evaluations reflected in scholarly book reviews and the citation frequencies of reviewed books. Results of the study designate a J-shaped distribution between the considered variables, presumably caused by a skewed allocation of negative citations. The paper concludes with suggestions for further research.

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Abstract

Reviews the scale, range and consistency of acknowledgement behaviour, in citations, for a number of academic disciplines. The qualitative and quantitative evidence suggests a pervasive and consistent practice in which acknowledgements define a variety of social, cognitive and instrumental relationships between scholars and within and across disciplines. As such they may be used alongside other bibliometric indicators, such as citations, to map networks of influence. Considers the case for using acknowledgements data in the assessment of academic performance and proposes an online acknowledgement index to facilitate this process, perhaps as a logical extension of ISI's citation indexing products

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Abstract

Systematic reviews are essential for evaluating biomedical treatment options, but the growing size and complexity of the available biomedical literature combined with the rigor of the systematic review method mean that systematic reviews are extremely difficult and labor-intensive to perform. In this article, I propose a method of searching the literature by systematically mining the various types of citation relationships between articles. I then test the method by comparing its precision and recall to that of 14 published systematic reviews. The method successfully retrieved 74% of the studies included in these reviews and 90% of the studies it could reasonably be expected to retrieve. The method also retrieved fewer than half of the total number of publications retrieved by these reviews and can be performed in substantially less time. This suggests that the proposed method offers a promising complement to traditional text-based methods of literature identification and retrieval for systematic reviews.

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Abstract

A citation index is a bibliographic database that provides citation links between documents. The first modern citation index was suggested by the researcher Eugene Garfield in 1955 and created by him in 1964, and it represents an important innovation to knowledge organization and information retrieval. This article describes citation indexes in general, considering the modern citation indexes, including Web of Science, Scopus, Google Scholar, Microsoft Academic, Crossref, Dimensions and some special citation indexes and predecessors to the modern citation index like Shepard's Citations. We present comparative studies of the major ones and survey theoretical problems related to the role of citation indexes as subject access points (SAP), recognizing the implications to knowledge organization and information retrieval. Finally, studies on citation behavior are presented and the influence of citation indexes on knowledge organization, information retrieval and the scientific information ecosystem is recognized.

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Abstract

In spite of numerous studies of citation behaviour and the wide recognition by journal editors of the need to acknowledge intellectual debts, authors and referees need explicit reminders as to when formal refrences or acknowledgements are appropriate. Notes a 3 year experiment involving graduate students which demonstrated the varying perceptions of the need for documentation off terminology, ideas and methods. Suggests a tentative tutorial for journal editors that should be modified in each scholarly context

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Abstract

Part 2 of a 2 part article reviewing the technique of bibliometrics and one of its most widely used methods, citation analysis. Reports on studies of author co-citation, periodical by periodical citation analysis and country by country citation analysis in addition to the mapping of science as an application of citation analysis. Considers the limitations, problems and reliability of citation analysis

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Abstract

Numerous attempts have been made to validate the use of citations as an evaluation method by comparing it with peer review. Unlike past studies using journals, research articles or universities as the subject matter, the present study extends the comparison to the ranking of individual scholars. Results show that citation ranking and expert judgement of communication scholars are highly correlated. The citation methods and the expert judgement method are found to work better in smaller research areas and yield more valid evaluation results for more prominent scholars

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Abstract

The accrual of symbolic capital is an important aspect of academic life. Successful capital formation is commonly signified by the trappings of scholarly distinction or acknowledged status as a public intellectual. We consider and compare three potential indices of symbolic capital: citation counts, Web hits, and media mentions. Our Eindings, which are domain specific, suggest that public intellectuals are notable by their absence within the information studies community.

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Abstract

Describes the construction of improved informetric models of individual scientific and technological areas on the basis of individual co citation clusters. The developed methodology of replenishment of research front with accidently absent papers describes the model more completely. Proposes the simple method of cluster 'dynamization' for the study of evolution of research area. The transition under consideration from co citation clusters to lexical maps of papers and patents enables the monitoring of the relationshuip between R and D in a given technological area. Provides the example from modern chemical engineering of Pressure-Swing Adsorption

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Abstract

In this paper we address the various formulations of impact of articles, usually groups of articles as gauged by citations that these articles receive over a certain period of time. The journal impact factor, as published by ISI (Philadelphia, PA), is the best-known example of a formulation of impact of journals (considered as a set of articles) but many others have been defined in the literature. Impact factors have varying publication and citation periods and the chosen length of these periods enables, e.g., a distinction between synchronous and diachronous impact factors. It is shown how an impact factor for the general case can be defined. Two alternatives for a general impact factor are proposed, depending an whether different publication years are seen as a whole, and hence treating each one of them differently, or by operating with citation periods of identical length but allowing each publication period different starting points.

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Abstract

The aggregated citation relations among journals included in the Science Citation Index provide us with a huge matrix, which can be analyzed in various ways. By using principal component analysis or factor analysis, the factor scores can be employed as indicators of the position of the cited journals in the citing dimensions of the database. Unrotated factor scores are exact, and the extraction of principal components can be made stepwise because the principal components are independent. Rotation may be needed for the designation, but in the rotated solution a model is assumed. This assumption can be legitimated on pragmatic or theoretical grounds. Because the resulting outcomes remain sensitive to the assumptions in the model, an unambiguous classification is no longer possible in this case. However, the factor-analytic solutions allow us to test classifications against the structures contained in the database; in this article the process will be demonstrated for the delineation of a set of biochemistry journals.

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Abstract

We present an analysis of data citation practices based on the Data Citation Index (DCI) (Thomson Reuters). This database launched in 2012 links data sets and data studies with citations received from the other citation indexes. The DCI harvests citations to research data from papers indexed in the Web of Science. It relies on the information provided by the data repository. The findings of this study show that data citation practices are far from common in most research fields. Some differences have been reported on the way researchers cite data: Although in the areas of science and engineering & technology data sets were the most cited, in the social sciences and arts & humanities data studies play a greater role. A total of 88.1% of the records have received no citation, but some repositories show very low uncitedness rates. Although data citation practices are rare in most fields, they have expanded in disciplines such as crystallography and genomics. We conclude by emphasizing the role that the DCI could play in encouraging the consistent, standardized citation of research data-a role that would enhance their value as a means of following the research process from data collection to publication.