186,201 research outputs found

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed

    Appropriate Similarity Measures for Author Cocitation Analysis

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    We provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis

    Withdrawn by Author

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    <p>Withdrawn by Author </p&gt

    Dispelling the Myths Behind First-author Citation Counts

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    We conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more sophisticated methods

    Dr. Edward P. Wimberly, ITC, July 2011

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    This video is a conversation with Dr. Edward P. Wimberly. Dr. Wimberly talks about his book, "No Shame in Wesley's Gospel: A Twenty-First Century Pastoral Gospel". Brad Ost, AUC Woodruff Library, is the interviewer

    Author Rights and Scholarly Publishing

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    Originally posted at http://blog.library.gsu.edu/2014/10/24/author-rights-and-scholarly-publishing/</p

    Acceptance and knowledge of evolutionary theory among third-year university students in Spain

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    The theory of evolution is one of the greatest scientific achievements in the intellectual history of humankind, yet it is still contentious within certain social groups. Despite being as robust and evidence-based as any other notable scientific theory, some people show a strong reluctance to accept it. In this study, we used the Measure of Acceptance of the Theory of Evolution (MATE) and Knowledge of Evolution Exam (KEE) questionnaires with university students from four academic degree programs (Chemistry, English, History, and Biology) of ten universities from Spain to measure, respectively, acceptance and knowledge of evolutionary theory among third-year undergraduate students (nMATE = 978; nKEE = 981). Results show that acceptance of evolution is relatively high (87.2%), whereas knowledge of the theory is moderate (5.4 out of 10) although there are differences across degrees (Biology>Chemistry>History>English), and even among various universities (ranging from 4.71 to 5.81). Statistical analysis reveals that knowledge of evolutionary theory among Biology students is partially explained by the relative weight of evolutionary themes within the curriculum, suggesting that an increase in the number of hours dedicated to this topic could have a direct influence on students’ knowledge of it. We also found that religion may have a significant—although relatively small—negative influence on evolutionary theory acceptance. The moderate knowledge of evolution in our undergraduate students, together with the potential problem of acceptance in certain groups, suggests the need for a revision of the evolutionary concepts in the teaching curricula of our students since primary school. © 2020 Gefaell et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Xunta de Galicia ED431C 2016-037Ministerio de Economía y Competitividad CGL2016-75904-C2-1-

    Mapping the Discipline of the Olympic Games An Author-Cocitation Analysis

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    The authors conducted an author cocitation analysis on prominent authors writing about the Olympics during the 1990s. Author cocitation is an established bibliometric technique that can be used to measure the relative similarities of topics written about by the cited authors. This enables a visual representation of the “intellectual space” of the discipline, in this case the Olympics, to be created for the period under review. So core and peripheral research areas are identified, along with their major contributors. The representation appears as a two-dimensional cluster-enhanced map. Subject expertise was then applied to the results to place labels on the generated clusters of authors and their topics
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