-
He, Y.; Hui, S.C.: PubSearch : a Web citation-based retrieval system (2001)
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- Abstract
- Many scientific publications are now available on the World Wide Web for researchers to share research findings. However, they tend to be poorly organised, making the search of relevant publications difficult and time-consuming. Most existing search engines are ineffective in searching these publications, as they do not index Web publications that normally appear in PDF (portable document format) or PostScript formats. Proposes a Web citation-based retrieval system, known as PubSearch, for the retrieval of Web publications. PubSearch indexes Web publications based on citation indices and stores them into a Web Citation Database. The Web Citation Database is then mined to support publication retrieval. Apart from supporting the traditional cited reference search, PubSearch also provides document clustering search and author clustering search. Document clustering groups related publications into clusters, while author clustering categorizes authors into different research areas based on author co-citation analysis.
-
Gorraiz, J.: "Web of Science" versus "Scopus" oder das aktuelle Dilemma der Bibliotheken (2006)
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- Abstract
- Bei den nachfolgenden Ausführungen handelt es sich um eine Zusammenstellung von Kommentaren, Vorträgen und Rückmeldungen von Kollegen bzw. Benutzern der Bibliothek sowie meine eigenen Erfahrungen als Vortragender im Universitätslehrgang "Master of Science", in dessen Rahmen ich das Fach "Bibliometrie" unterrichte. Schwerpunkt dieses Beitrages ist eine Zusammenfassung der Diskussion "Web of Science versus Scopus", die den aktuellen Stand der Kontroverse (vor allem an der Universität Wien im naturwissenschaftlichen Sektor) widerspiegelt. Hier ist zu bemerken, dass diese Problematik auch fachspezifisch ist und deswegen an jeder Universität bzw. in jedem Fachgebiet anders zu betrachten ist. Startpunkt meiner Betrachtung ist die allgemein akzeptierte Notwendigkeit des "Journal of Citation Reports (JCR)". Nur in diesem bibliometrischen Verzeichnis sind derzeit die "Impact Factors" zu finden, die als Grundlage jeder akademischen Evaluation dienen. Deswegen ist JCR heutzutage an jeder Universität mit naturwissenschaftlichen Fächern unentbehrlich und das aktuelle Dilemma der Bibliothekare lautet nicht wirklich "Web of Science versus Scopus", sondern genaugesagt "Fallbeispiel A: Web of Science &JCR" oder "Fallbeispiel B: Scopus &JCR".
- Object
- Web of Science
-
H-Index auch im Web of Science (2008)
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- Content
- "Zur Kurzmitteilung "Latest enhancements in Scopus: ... h-Index incorporated in Scopus" in den letzten Online-Mitteilungen (Online-Mitteilungen 92, S.31) ist zu korrigieren, dass der h-Index sehr wohl bereits im Web of Science enthalten ist. Allerdings findet man/frau diese Information nicht in der "cited ref search", sondern neben der Trefferliste einer Quick Search, General Search oder einer Suche über den Author Finder in der rechten Navigationsleiste unter dem Titel "Citation Report". Der "Citation Report" bietet für die in der jeweiligen Trefferliste angezeigten Arbeiten: - Die Gesamtzahl der Zitierungen aller Arbeiten in der Trefferliste - Die mittlere Zitationshäufigkeit dieser Arbeiten - Die Anzahl der Zitierungen der einzelnen Arbeiten, aufgeschlüsselt nach Publikationsjahr der zitierenden Arbeiten - Die mittlere Zitationshäufigkeit dieser Arbeiten pro Jahr - Den h-Index (ein h-Index von x sagt aus, dass x Arbeiten der Trefferliste mehr als x-mal zitiert wurden; er ist gegenüber sehr hohen Zitierungen einzelner Arbeiten unempfindlicher als die mittlere Zitationshäufigkeit)."
- Date
- 6. 4.2008 19:04:22
- Object
- Web of Science
-
Ahlgren, P.; Jarneving, B.; Rousseau, R.: Requirements for a cocitation similarity measure, with special reference to Pearson's correlation coefficient (2003)
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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
- Source
- Journal of the American Society for Information Science and technology. 54(2003) no.6, S.549-568
-
Vaughan, L.; Shaw , D.: Bibliographic and Web citations : what Is the difference? (2003)
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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.
- Source
- Journal of the American Society for Information Science and technology. 54(2003) no.14, S.1313-1324
-
He, Y.; Hui, S.C.: Mining a web database for author cocitation analysis (2002)
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- Source
- Information processing and management. 38(2002) no.4, S.491-508
-
Cronin, B.: Bibliometrics and beyond : some thoughts on web-based citation analysis (2001)
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- Source
- Journal of information science. 27(2001) no.1, S.1-7
-
Smith, A.G.: Web links as analogues of citations (2004)
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- Source
- Information Research. 9(2004), no.4
-
Vaughan, L.; Shaw, D.: Web citation data for impact assessment : a comparison of four science disciplines (2005)
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- Abstract
- The number and type of Web citations to journal articles in four areas of science are examined: biology, genetics, medicine, and multidisciplinary sciences. For a sample of 5,972 articles published in 114 journals, the median Web citation counts per journal article range from 6.2 in medicine to 10.4 in genetics. About 30% of Web citations in each area indicate intellectual impact (citations from articles or class readings, in contrast to citations from bibliographic services or the author's or journal's home page). Journals receiving more Web citations also have higher percentages of citations indicating intellectual impact. There is significant correlation between the number of citations reported in the databases from the Institute for Scientific Information (ISI, now Thomson Scientific) and the number of citations retrieved using the Google search engine (Web citations). The correlation is much weaker for journals published outside the United Kingdom or United States and for multidisciplinary journals. Web citation numbers are higher than ISI citation counts, suggesting that Web searches might be conducted for an earlier or a more fine-grained assessment of an article's impact. The Web-evident impact of non-UK/USA publications might provide a balance to the geographic or cultural biases observed in ISI's data, although the stability of Web citation counts is debatable.
- Source
- Journal of the American Society for Information Science and Technology. 56(2005) no.10, S.1075-1087
-
Kousha, K.; Thelwall, M.: Google Scholar citations and Google Web/URL citations : a multi-discipline exploratory analysis (2007)
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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.
- Source
- Journal of the American Society for Information Science and Technology. 58(2007) no.7, S.1055-1065
-
Thelwall, M.; Vaughan, L.; Björneborn, L.: Webometrics (2004)
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- Abstract
- Webometrics, the quantitative study of Web-related phenomena, emerged from the realization that methods originally designed for bibliometric analysis of scientific journal article citation patterns could be applied to the Web, with commercial search engines providing the raw data. Almind and Ingwersen (1997) defined the field and gave it its name. Other pioneers included Rodriguez Gairin (1997) and Aguillo (1998). Larson (1996) undertook exploratory link structure analysis, as did Rousseau (1997). Webometrics encompasses research from fields beyond information science such as communication studies, statistical physics, and computer science. In this review we concentrate on link analysis, but also cover other aspects of webometrics, including Web log fle analysis. One theme that runs through this chapter is the messiness of Web data and the need for data cleansing heuristics. The uncontrolled Web creates numerous problems in the interpretation of results, for instance, from the automatic creation or replication of links. The loose connection between top-level domain specifications (e.g., com, edu, and org) and their actual content is also a frustrating problem. For example, many .com sites contain noncommercial content, although com is ostensibly the main commercial top-level domain. Indeed, a skeptical researcher could claim that obstacles of this kind are so great that all Web analyses lack value. As will be seen, one response to this view, a view shared by critics of evaluative bibliometrics, is to demonstrate that Web data correlate significantly with some non-Web data in order to prove that the Web data are not wholly random. A practical response has been to develop increasingly sophisticated data cleansing techniques and multiple data analysis methods.
- Source
- Annual review of information science and technology. 39(2005), S.81-138
-
Larivière, V.; Gingras, Y.; Archambault, E.: ¬The decline in the concentration of citations, 1900-2007 (2009)
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- Abstract
- This article challenges recent research (Evans, 2008) reporting that the concentration of cited scientific literature increases with the online availability of articles and journals. Using Thomson Reuters' Web of Science, the present article analyses changes in the concentration of citations received (2- and 5-year citation windows) by papers published between 1900 and 2005. Three measures of concentration are used: the percentage of papers that received at least one citation (cited papers); the percentage of papers needed to account for 20%, 50%, and 80% of the citations; and the Herfindahl-Hirschman index (HHI). These measures are used for four broad disciplines: natural sciences and engineering, medical fields, social sciences, and the humanities. All these measures converge and show that, contrary to what was reported by Evans, the dispersion of citations is actually increasing.
- Date
- 22. 3.2009 19:22:35
- Source
- Journal of the American Society for Information Science and Technology. 60(2009) no.4, S.858-862
-
Prime-Claverie, C.; Beigbeder, M.; Lafouge, T.: Transposition of the cocitation method with a view to classifying Web pages (2004)
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- Abstract
- The Web is a huge source of information, and one of the main problems facing users is finding documents which correspond to their requirements. Apart from the problem of thematic relevance, the documents retrieved by search engines do not always meet the users' expectations. The document may be too general, or conversely too specialized, or of a different type from what the user is looking for, and so forth. We think that adding metadata to pages can considerably improve the process of searching for information an the Web. This article presents a possible typology for Web sites and pages, as weIl as a method for propagating metadata values, based an the study of the Web graph and more specifically the method of cocitation in this graph.
- Source
- Journal of the American Society for Information Science and Technology. 55(2004) no.14, S.1282-1289
-
Stock, W.G.: Eugene Garfield und die Folgen : der Weg der Fußnote bis in die Wissenschaftspolitik (2002)
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- Abstract
- Ein Besprechungsaufsatz zur Festschrift für E. Garfield: The Web of knowledge: Festschrift in honor of Eugene Garfield. Medford, NJ: Information Today 2000.
-
McVeigh, M.E.: Citation indexes and the Web of Science (2009)
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- Abstract
- The Web of Science, an online database of bibliographic information produced by Thomson Reuters- draws its real value from the scholarly citation index at its core. By indexing the cited references from each paper as a separate part of the bibliographic data, a citation index creates a pathway by which a paper can be linked backward in time to the body of work that preceded it, as well as linked forward in time to its scholarly descendants. This entry provides a brief history of the development of the citation index, its core functionalities, and the way these unique data are provided to users through the Web of Science.
- Object
- Web of Science
- Source
- Encyclopedia of library and information sciences. 3rd ed. Ed.: M.J. Bates
-
Thelwall, M.: Extracting macroscopic information from Web links (2001)
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- Abstract
- Much has been written about the potential and pitfalls of macroscopic Web-based link analysis, yet there have been no studies that have provided clear statistical evidence that any of the proposed calculations can produce results over large areas of the Web that correlate with phenomena external to the Internet. This article attempts to provide such evidence through an evaluation of Ingwersen's (1998) proposed external Web Impact Factor (WIF) for the original use of the Web: the interlinking of academic research. In particular, it studies the case of the relationship between academic hyperlinks and research activity for universities in Britain, a country chosen for its variety of institutions and the existence of an official government rating exercise for research. After reviewing the numerous reasons why link counts may be unreliable, it demonstrates that four different WIFs do, in fact, correlate with the conventional academic research measures. The WIF delivering the greatest correlation with research rankings was the ratio of Web pages with links pointing at research-based pages to faculty numbers. The scarcity of links to electronic academic papers in the data set suggests that, in contrast to citation analysis, this WIF is measuring the reputations of universities and their scholars, rather than the quality of their publications
- Source
- Journal of the American Society for Information Science and technology. 52(2001) no.13, S.1157-1168
-
Whitley, K.M.: Analysis of SciFinder Scholar and Web of Science citation searches (2002)
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- Abstract
- Chemical Abstracts Service recently unveiled citation searching in Chemical Abstracts. With Chemical Abstracts and Science Citation Index both now available for citation searching, this study compares the duplication and uniqueness of citing references for works of chemistry researchers for the years 1999-2001. The two indexes cover very similar source material, so one would expect the citation results to be very similar. This analysis of SciFinder Scholar and Web of Science shows some important differences as the databases are currently offered. Authors and institutions using citation counts as measures of scientific productivity should take note.
- Object
- Web of science
- Source
- Journal of the American Society for Information Science and technology. 53(2002) no.14, S.1210-1215
-
Brody, T.; Harnad, S.; Carr, L.: Earlier Web usage statistics as predictors of later citation impact (2006)
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- Abstract
- The use of citation counts to assess the impact of research articles is well established. However, the citation impact of an article can only be measured several years after it has been published. As research articles are increasingly accessed through the Web, the number of times an article is downloaded can be instantly recorded and counted. One would expect the number of times an article is read to be related both to the number of times it is cited and to how old the article is. The authors analyze how short-term Web usage impact predicts medium-term citation impact. The physics e-print archive-arXiv.org-is used to test this.
- Source
- Journal of the American Society for Information Science and Technology. 57(2006) no.8, S.1060-1072
-
Zhao, D.: Challenges of scholarly publications on the Web to the evaluation of science : a comparison of author visibility on the Web and in print journals (2005)
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- Abstract
- This article reveals different patterns of scholarly communication in the XML research field on the Web and in print journals in terms of author visibility, and challenges the common practice of exclusively using the ISI's databases to obtain citation counts as scientific performance indicators. Results from this study demonstrate both the importance and the feasibility of the use of multiple citation data sources in citation analysis studies of scholarly communication, and provide evidence for a developing "two tier" scholarly communication system.
- Source
- Information processing and management. 41(2005) no.6, S.1403-1418
-
Larsen, B.: Exploiting citation overlaps for information retrieval : generating a boomerang effect from the network of scientific papers (2002)
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