Search (141 results, page 1 of 8)

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Abstract

Webometric network analyses have been used to map the connectivity of groups of websites to identify clusters, important sites or overall structure. Such analyses have mainly been based upon hyperlink counts, the number of hyperlinks between a pair of websites, although some have used title mentions or URL citations instead. The ability to automatically gather hyperlink counts from Yahoo! ceased in April 2011 and the ability to manually gather such counts was due to cease by early 2012, creating a need for alternatives. This article assesses URL citations and title mentions as possible replacements for hyperlinks in both binary and weighted direct link and co-inlink network diagrams. It also assesses three different types of data for the network connections: hit count estimates, counts of matching URLs, and filtered counts of matching URLs. Results from analyses of U.S. library and information science departments and U.K. universities give evidence that metrics based upon URLs or titles can be appropriate replacements for metrics based upon hyperlinks for both binary and weighted networks, although filtered counts of matching URLs are necessary to give the best results for co-title mention and co-URL citation network diagrams.

Date

6. 4.2012 18:16:22

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Abstract

This study comprises a suite of analyses of words in article titles in order to reveal the cognitive structure of Library and Information Science (LIS). The use of title words to elucidate the cognitive structure of LIS has been relatively neglected. The present study addresses this gap by performing (a) co-word analysis and hierarchical clustering, (b) multidimensional scaling, and (c) determination of trends in usage of terms. The study is based on 10,344 articles published between 1988 and 2007 in 16 LIS journals. Methodologically, novel aspects of this study are: (a) its large scale, (b) removal of non-specific title words based on the "word concentration" measure (c) identification of the most frequent terms that include both single words and phrases, and (d) presentation of the relative frequencies of terms using "heatmaps". Conceptually, our analysis reveals that LIS consists of three main branches: the traditionally recognized library-related and information-related branches, plus an equally distinct bibliometrics/scientometrics branch. The three branches focus on: libraries, information, and science, respectively. In addition, our study identifies substructures within each branch. We also tentatively identify "information seeking behavior" as a branch that is establishing itself separate from the three main branches. Furthermore, we find that cognitive concepts in LIS evolve continuously, with no stasis since 1992. The most rapid development occurred between 1998 and 2001, influenced by the increased focus on the Internet. The change in the cognitive landscape is found to be driven by the emergence of new information technologies, and the retirement of old ones.

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Abstract

The primary webometric method for estimating the online impact of an organization is to count links to its website. Link counts have been available from commercial search engines for over a decade but this was set to end by early 2012 and so a replacement is needed. This article compares link counts to two alternative methods: URL citations and organization title mentions. New variations of these methods are also introduced. The three methods are compared against each other using Yahoo!. Two of the three methods (URL citations and organization title mentions) are also compared against each other using Bing. Evidence from a case study of 131 UK universities and 49 US Library and Information Science (LIS) departments suggests that Bing's Hit Count Estimates (HCEs) for popular title searches are not useful for webometric research but that Yahoo!'s HCEs for all three types of search and Bing's URL citation HCEs seem to be consistent. For exact URL counts the results of all three methods in Yahoo! and both methods in Bing are also consistent. Four types of accuracy factors are also introduced and defined: search engine coverage, search engine retrieval variation, search engine retrieval anomalies, and query polysemy.

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Abstract

This paper explores the ISI Journal Citation Reports (JCR) bibliographic and subject structures through Library of Congress (LC) and American research libraries cataloging and classification methodology. The 2006 Science Citation Index JCR Behavioral Sciences subject category journals are used as an example. From the library perspective, the main fault of the JCR bibliographic structure is that the JCR mistakenly identifies journal title segments as journal bibliographic entities, seriously affecting journal rankings by total cites and the impact factor. In respect to JCR subject structure, the title segment, which constitutes the JCR bibliographic basis, is posited as the best bibliographic entity for the citation measurement of journal subject relationships. Through factor analysis and other methods, the JCR subject categorization of journals is tested against their LC subject headings and classification. The finding is that JCR and library journal subject analyses corroborate, clarify, and correct each other.

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Abstract

Fields of technoscience like biotechnology develop in a network mode: disciplinary insights from different backgrounds are recombined as competing innovation systems are continuously reshaped. The ongoing process of integration at the European level generates an additional network of transnational collaborations. Using the title words of scientific publications in five core journals of biotechnology, multivariate analysis is used to distinguish between the intellectual organization of the publications in terms of title words and the institutional network in terms of addresses of documents. The interaction among the representation of intellectual space in terms of words and co-words, and the potentially European network system is compared with the document sets with American and Japanese addresses. The European system can also be decomposed in terms of the contributions of member states. Whereas a European vocabulary can be made visible at the global level, this communality disappears by this decomposition. The network effect at the European level can be considered as institutional more than cognitive

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Abstract

Vaughn, and Shaw look at the relationship between traditional citation and Web citation (not hyperlinks but rather textual mentions of published papers). Using English language research journals in ISI's 2000 Journal Citation Report - Information and Library Science category - 1209 full length papers published in 1997 in 46 journals were identified. Each was searched in Social Science Citation Index and on the Web using Google phrase search by entering the title in quotation marks, and followed for distinction where necessary with sub-titles, author's names, and journal title words. After removing obvious false drops, the number of web sites was recorded for comparison with the SSCI counts. A second sample from 1992 was also collected for examination. There were a total of 16,371 web citations to the selected papers. The top and bottom ranked four journals were then examined and every third citation to every third paper was selected and classified as to source type, domain, and country of origin. Web counts are much higher than ISI citation counts. Of the 46 journals from 1997, 26 demonstrated a significant correlation between Web and traditional citation counts, and 11 of the 15 in the 1992 sample also showed significant correlation. Journal impact factor in 1998 and 1999 correlated significantly with average Web citations per journal in the 1997 data, but at a low level. Thirty percent of web citations come from other papers posted on the web, and 30percent from listings of web based bibliographic services, while twelve percent come from class reading lists. High web citation journals often have web accessible tables of content.

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Abstract

When using scientific literature to model scholarly discourse, a research specialty can be operationalized as an evolving set of related documents. Each publication can be expected to contribute to the further development of the specialty at the research front. The specific combinations of title words and cited references in a paper can then be considered as a signature of the knowledge claim in the paper: New words and combinations of words can be expected to represent variation, while each paper is at the same time selectively positioned into the intellectual organization of a field using context-relevant references. Can the mutual information among these three dimensions - title words, cited references, and sequence numbers - be used as an indicator of the extent to which intellectual organization structures the uncertainty prevailing at a research front? The effect of the discovery of nanotubes (1991) on the previously existing field of fullerenes is used as a test case. Thereafter, this method is applied to science studies with a focus on scientometrics using various sample delineations. An emerging research front about citation analysis can be indicated.

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Abstract

This study investigated name changes of women authors to determine how they were represented in indexes and cited references and identify problem areas. A secondary purpose of the study was to investigate whether or not indexing services were using authority control and how this influenced the search results. The works of eight library science authors who had published under multiple names were examined. The researchers compared author names as they appeared on title pages of publications versus in four online databases and in bibliographies by checking 380 publications and 1,159 citations. Author names were correctly provided 81.22% of the time in indexing services and 90.94% in citation lists. The lowest accuracy (54.55%) occurred when limiting to publications found in Library Literature. The highest accuracy (94.18%) occurred with works published before a surname changed. Author names in indexes and citations correctly matched names on journal articles more often than for any other type of publication. Indexes and citation style manuals treated author names in multiple ways, often altering names substantially from how they appear on the title page. Recommendations are made for changes in editorial styles by indexing services and by the authors themselves to help alleviate future confusion in author name searching.

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Abstract

Assignability of authors to Web pages using either normal browsing procedures or browsing assisted by simple automatic extraction was investigated. Candidate strings for 1000 pages were extracted automatically from title elements, meta-tags, and address-like and copyright-like passages; 539 of the pages produced at least one candidate: 310 candidates from titles, 66 from meta-tags, 91 from address-like passages, and 259 from copyright-like passages. An assistant attempted to identify personal authors for 943 pages by examining the pages themselves and related pages; this added 90 pages with authors to the pages from which no candidate strings were extracted. Specific problems are noted and some refinements to the extraction methods are suggested.

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Abstract

We present a model for estimating the probability that a pair of author names (sharing last name and first initial), appearing an two different Medline articles, refer to the same individual. The model uses a simple yet powerful similarity profile between a pair of articles, based an title, journal name, coauthor names, medical subject headings (MeSH), language, affiliation, and name attributes (prevalence in the literature, middle initial, and suffix). The similarity profile distribution is computed from reference sets consisting of pairs of articles containing almost exclusively author matches versus nonmatches, generated in an unbiased manner. Although the match set is generated automatically and might contain a small proportion of nonmatches, the model is quite robust against contamination with nonmatches. We have created a free, public service ("Author-ity": http://arrowsmith.psych.uic.edu) that takes as input an author's name given an a specific article, and gives as output a list of all articles with that (last name, first initial) ranked by decreasing similarity, with match probability indicated.

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Abstract

Can the journal impact factors regularly published in the Journal Citation Reports (JCR) be shaped by a self-fulfilling prophecy? This question was investigated by reference to a journal for which incorrect impact factors had been published in the JCR for almost 20 years: Educational Research. In order to investigate whether the propagation of exaggerated impact factors had resulted in an increase in the actual impact of the journal, the correct impact factors were calculated. A self-fulfilling prophecy effect was not observed. However, shows that the impact factors for Educational Research published in the JCR were based on calculations that erroneously included citations of a journal with a similar title, Educational Researcher, which is not included in the JCR. Concludes that published impact factors should be used with caution.

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Abstract

Using the 138,751 patents filed in 2006 under the Patent Cooperation Treaty, co-classification analysis is pursued on the basis of three- and four-digit codes in the International Patent Classification (IPC, 8th ed.). The co-classifications among the patents enable us to analyze and visualize the relations among technologies at different levels of aggregation. The hypothesis that classifications might be considered as the organizers of patents into classes, and therefore that co-classification patterns - more than co-citation patterns - might be useful for mapping, is not corroborated. The classifications hang weakly together, even at the four-digit level; at the country level, more specificity can be made visible. However, countries are not the appropriate units of analysis because patent portfolios are largely similar in many advanced countries in terms of the classes attributed. Instead of classes, one may wish to explore the mapping of title words as a better approach to visualize the intellectual organization of patents.

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Abstract

Purpose - The purpose of this paper is to clarify earlier work on journal diffusion metrics. Classical journal indicators such as the Garfield impact factor do not measure the breadth of influence across the literature of a particular journal title. As a new approach to measuring research influence, the study complements these existing metrics with a series of formally described diffusion factors. Design/methodology/approach - Using a publication-citation matrix as an organising construct, the paper develops formal descriptions of two forms of diffusion metric: "relative diffusion factors" and "journal diffusion factors" in both their synchronous and diachronous forms. It also provides worked examples for selected library and information science and economics journals, plus a sample of health information papers to illustrate their construction and use. Findings - Diffusion factors capture different aspects of the citation reception process than existing bibliometric measures. The paper shows that diffusion factors can be applied at the whole journal level or for sets of articles and that they provide a richer evidence base for citation analyses than traditional measures alone. Research limitations/implications - The focus of this paper is on clarifying the concepts underlying diffusion factors and there is unlimited scope for further work to apply these metrics to much larger and more comprehensive data sets than has been attempted here. Practical implications - These new tools extend the range of tools available for bibliometric, and possibly webometric, analysis. Diffusion factors might find particular application in studies where the research questions focus on the dynamic aspects of innovation and knowledge transfer. Originality/value - This paper will be of interest to those with theoretical interests in informetric distributions as well as those interested in science policy and innovation studies.

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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

We use a new data gathering method, "Web/URL citation," Web/URL and Google Scholar to compare traditional and Web-based citation patterns across multiple disciplines (biology, chemistry, physics, computing, sociology, economics, psychology, and education) based upon a sample of 1,650 articles from 108 open access (OA) journals published in 2001. A Web/URL citation of an online journal article is a Web mention of its title, URL, or both. For each discipline, except psychology, we found significant correlations between Thomson Scientific (formerly Thomson ISI, here: ISI) citations and both Google Scholar and Google Web/URL citations. Google Scholar citations correlated more highly with ISI citations than did Google Web/URL citations, indicating that the Web/URL method measures a broader type of citation phenomenon. Google Scholar citations were more numerous than ISI citations in computer science and the four social science disciplines, suggesting that Google Scholar is more comprehensive for social sciences and perhaps also when conference articles are valued and published online. We also found large disciplinary differences in the percentage overlap between ISI and Google Scholar citation sources. Finally, although we found many significant trends, there were also numerous exceptions, suggesting that replacing traditional citation sources with the Web or Google Scholar for research impact calculations would be problematic.

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Abstract

This paper proposes a methodology which discriminates the articles by the target authors ("true" articles) from those by other homonymous authors ("false" articles). Author name searches for 2,595 "source" authors in six subject fields retrieved about 629,000 articles. In order to extract true articles from the large amount of the retrieved articles, including many false ones, two filtering stages were applied. At the first stage any retrieved article was eliminated as false if either its affiliation addresses had little similarity to those of its source article or there was no citation relationship between the journal of the retrieved article and that of its source article. At the second stage, a sample of retrieved articles was subjected to manual judgment, and utilizing the judgment results, discrimination functions based on logistic regression were defined. These discrimination functions demonstrated both the recall ratio and the precision of about 95% and the accuracy (correct answer ratio) of 90-95%. Existence of common coauthor(s), address similarity, title words similarity, and interjournal citation relationships between the retrieved and source articles were found to be the effective discrimination predictors. Whether or not the source author was from a specific country was also one of the important predictors. Furthermore, it was shown that a retrieved article is almost certainly true if it was cited by, or cocited with, its source article. The method proposed in this study would be effective when dealing with a large number of articles whose subject fields and affiliation addresses vary widely.

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Abstract

International collaborative papers are increasingly common in journals of many disciplines. These types of papers are often cited more frequently. To identify the coauthorship trends within Library and Information Science (LIS), this study analyzed 7,489 papers published in six leading publications (ARIST, IP&M, JAMIA, JASIST, MISQ, and Scientometrics) over the last three decades. Logistic regression tested the relationships between citations received and seven factors: authorship type, author's subregion, country income level, publication year, number of authors, document type, and journal title. The main authorship type since 1995 was national collaboration. It was also the dominant type for all publications studied except ARIST, and for all regions except Africa. For citation counts, the logistic regression analysis found all seven factors were significant. Papers that included international collaboration, Northern European authors, and authors in high-income nations had higher odds of being cited more. Papers from East Asia, Southeast Asia, and Southern Europe had lower odds than North American papers. As discussed in the bibliometric literature, Merton's Matthew Effect sheds light on the differential citation counts based on the authors' subregion. This researcher proposes geographies of invisible colleagues and a geographic scope effect to further investigate the relationships between author geographic affiliation and citation impact.

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Abstract

We present a new, two-stage, self-supervised algorithm for author disambiguation in large bibliographic databases. In the first "bootstrap" stage, a collection of high-precision features is used to bootstrap a training set with positive and negative examples of coreferring authors. A supervised feature-based classifier is then trained on the bootstrap clusters and used to cluster the authors in a larger unlabeled dataset. Our self-supervised approach shares the advantages of unsupervised approaches (no need for expensive hand labels) as well as supervised approaches (a rich set of features that can be discriminatively trained). The algorithm disambiguates 54,000,000 author instances in Thomson Reuters' Web of Knowledge with B3 F1 of.807. We analyze parameters and features, particularly those from citation networks, which have not been deeply investigated in author disambiguation. The most important citation feature is self-citation, which can be approximated without expensive extraction of the full network. For the supervised stage, the minor improvement due to other citation features (increasing F1 from.748 to.767) suggests they may not be worth the trouble of extracting from databases that don't already have them. A lean feature set without expensive abstract and title features performs 130 times faster with about equal F1.

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Abstract

This study examines a range of factors associated with future citation and altmetric counts to a paper. The factors include journal impact factor, individual collaboration, international collaboration, institution prestige, country prestige, research funding, abstract readability, abstract length, title length, number of cited references, field size, and field type and will be modeled in association with citation counts, Mendeley readers, Twitter posts, Facebook posts, blog posts, and news posts. The results demonstrate that eight factors are important for increased citation counts, seven different factors are important for increased Mendeley readers, eight factors are important for increased Twitter posts, three factors are important for increased Facebook posts, six factors are important for increased blog posts, and five factors are important for increased news posts. Journal impact factor and international collaboration are the two factors that significantly associate with increased citation counts and with all altmetric scores. Moreover, it seems that the factors driving Mendeley readership are similar to those driving citation counts. However, the altmetric events differ from each other in terms of a small number of factors; for instance, institution prestige and country prestige associate with increased Mendeley readers and blog and news posts, but it is an insignificant factor for Twitter and Facebook posts. The findings contribute to the continued development of theoretical models and methodological developments associated with capturing, interpreting, and understanding altmetric events.

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Abstract

Just as citations to a book can be counted, so can that book's libcitations-the number of libraries in a consortium that hold it. These holdings counts per title can be obtained from the consortium's union catalog, such as OCLC's WorldCat. Librarians seeking to serve their customers well must be attuned to various kinds of merit in books. The result in WorldCat is a great variation in the libcitations particular books receive. The higher a title's count (or percentile), the more famous it is-either absolutely or within a subject class. Degree of fame also indicates cultural impact, allowing that further documentation of impact may be needed. Using WorldCat data, we illustrate high, medium, and low degrees of fame with 170 titles published during 1990-1995 or 2001-2006 and spanning the 10 main Dewey classes. We use their total libcitation counts or their counts from members of the Association of Research Libraries, or both, as of late 2011. Our analysis of their fame draws on the recognizability of their authors, the extent to which they and their authors are covered by Wikipedia, and whether they have movie or TV versions. Ordinal scales based on Wikipedia coverage and on libcitation counts are very significantly associated.