25 research outputs found

    Scholarly E-book Across Disciplines: Content Analysis of Usage Reports and Search Terms

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    This presentation was offered as part of the CUNY Library Assessment Conference, Reinventing Libraries: Reinventing Assessment, held at the City University of New York in June 2014

    Three options for citation tracking: Google Scholar, Scopus and Web of Science

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    BACKGROUND: Researchers turn to citation tracking to find the most influential articles for a particular topic and to see how often their own published papers are cited. For years researchers looking for this type of information had only one resource to consult: the Web of Science from Thomson Scientific. In 2004 two competitors emerged – Scopus from Elsevier and Google Scholar from Google. The research reported here uses citation analysis in an observational study examining these three databases; comparing citation counts for articles from two disciplines (oncology and condensed matter physics) and two years (1993 and 2003) to test the hypothesis that the different scholarly publication coverage provided by the three search tools will lead to different citation counts from each. METHODS: Eleven journal titles with varying impact factors were selected from each discipline (oncology and condensed matter physics) using the Journal Citation Reports (JCR). All articles published in the selected titles were retrieved for the years 1993 and 2003, and a stratified random sample of articles was chosen, resulting in four sets of articles. During the week of November 7–12, 2005, the citation counts for each research article were extracted from the three sources. The actual citing references for a subset of the articles published in 2003 were also gathered from each of the three sources. RESULTS: For oncology 1993 Web of Science returned the highest average number of citations, 45.3. Scopus returned the highest average number of citations (8.9) for oncology 2003. Web of Science returned the highest number of citations for condensed matter physics 1993 and 2003 (22.5 and 3.9 respectively). The data showed a significant difference in the mean citation rates between all pairs of resources except between Google Scholar and Scopus for condensed matter physics 2003. For articles published in 2003 Google Scholar returned the largest amount of unique citing material for oncology and Web of Science returned the most for condensed matter physics. CONCLUSION: This study did not identify any one of these three resources as the answer to all citation tracking needs. Scopus showed strength in providing citing literature for current (2003) oncology articles, while Web of Science produced more citing material for 2003 and 1993 condensed matter physics, and 1993 oncology articles. All three tools returned some unique material. Our data indicate that the question of which tool provides the most complete set of citing literature may depend on the subject and publication year of a given article

    A social network analysis of research collaboration in the economics community

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    RePEc (Research Papers in Economics) offers the RePEc Author Service (RAS). It allows registrants to claim authorship of the research papers that are described in RePEc archives. The data from this service forms a highquality authorship database. We use this data to examine, as a practical example, how different network constructions affect the ranking of economists through authorship centrality. We use Spearman's rho test for evaluating the correlation between author centrality measures

    Developing a predictive model of editor selectivity in a current awareness service of a large digital library

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    “NEP: New Economics Papers,” the current awareness service for the RePEc (Research Papers in Economics) digital library, is made possible by volunteer editors who filter new additions to RePEc into subject-specific reports. The official purpose of current awareness service is to filter working papers by subject matter without any judgment of its academic quality. In this article binary logistic regression analysis estimates the probability of a paper being included in any of the subject reports as a function of a range of observable values. The analysis suggests that, contrary to their claims, editors use quality criteria: the series the paper is coming from and the reputation of the authors. The findings suggest that a current awareness service can issue quality signals

    Metadata characteristics as predictors for editor selectivity in a current awareness service

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    RePEc is a large digital library for the economics community. “NEP: New Economics Papers” is a current awareness service for recent additions to RePEc. The service is run by volunteer editors. They filter new additions to RePEc into subject-specific reports. The intended purpose of this current awareness service is to filter papers by subject matter without any judgment of their academic quality. We use binary logistic regression analysis to estimate the probability of a paper being included in any of the subject reports as a function of a range of observable variables. Our analysis suggests that, contrary to their own claims, editors use quality criteria. These include the reputation of the series as well as the reputation of the authors. Our findings suggest that a current awareness service can be used as a first step of a peer-review process
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