165,764 research outputs found
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe 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
Mapping the Discipline of the Olympic Games An Author-Cocitation Analysis
No full textThe 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
Author Co-Citation Analysis (ACA): a powerful tool for representing implicit knowledge of scholar knowledge workers
No full textIn the last decade, knowledge has emerged as one of the most important and valuable organizational assets. Gradually this importance caused to emergence of new discipline entitled ―knowledge management‖. However one of the major challenges of knowledge management is conversion implicit or tacit knowledge to explicit knowledge. Thus Making knowledge visible so that it can be better accessed, discussed, valued or generally managed is a long-standing objective in knowledge management. Accordingly in this paper author co- citation analysis (ACA) will be proposed as an efficient technique of knowledge visualization in academia (Scholar knowledge workers)
Co-citation Analysis: An Overview
No full textThis article gives an overview of co-citation analysis and its applications in tracking the linkages among the intellectual works and mapping the evolutionary structure of scientific disciplines. It also focuses on the features, interface, terminology used, merits and demerits of co-citation based online database applications
Appropriate Similarity Measures for Author Cocitation Analysis
No full textWe 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
Some Comments on the Question Whether Co-occurrence Data Should Be Normalized
No full textIn a recent paper in the Journal of the American Society for Information Science and Technology, Leydesdorff and Vaughan assert that raw cocitation data should be analyzed directly, without first applying a normalization like the Pearson correlation. In this report, it is argued that there is nothing wrong with the widely adopted practice of normalizing cocitation data. One of the arguments put forward by Leydesdorff and Vaughan turns out to depend crucially on incorrect multidimensional scaling maps that are due to an error in the PROXSCAL program in SPSS.Multidimensional scaling;Author cocitation analysis;Co-occurrence data;Normalization;PROXSCAL;Pearson correlation
Open access self-archiving: An author study
No full textThis, our second author international, cross-disciplinary study on open access had 1296 respondents. Its focus was on self-archiving. Almost half (49%) of the respondent population have self-archived at least one article during the last three years. Use of institutional repositories for this purpose has doubled and usage has increased by almost 60% for subject-based repositories. Self-archiving activity is greatest amongst those who publish the largest number of papers. There is still a substantial proportion of authors unaware of the possibility of providing open access to their work by self-archiving. Of the authors who have not yet self-archived any articles, 71% remain unaware of the option. With 49% of the author population having self-archived in some way, this means that 36% of the total author population (71% of the remaining 51%), has not yet been appraised of this way of providing open access. Authors have frequently expressed reluctance to self-archive because of the perceived time required and possible technical difficulties in carrying out this activity, yet findings here show that only 20% of authors found some degree of difficulty with the first act of depositing an article in a repository, and that this dropped to 9% for subsequent deposits. Another author worry is about infringing agreed copyright agreements with publishers, yet only 10% of authors currently know of the SHERPA/RoMEO list of publisher permissions policies with respect to self-archiving, where clear guidance as to what a publisher permits is provided. Where it is not known if permission is required, however, authors are not seeking it and are self-archiving without it. Communicating their results to peers remains the primary reason for scholars publishing their work; in other words,
researchers publish to have an impact on their field. The vast majority of authors (81%) would willingly comply with a mandate from their employer or research funder to deposit copies of their articles in an institutional or subject-based repository. A further 13% would comply reluctantly; 5% would not comply with such a mandate
Co-authorship network of authors selected papers, source: Formulated by author using VOS viewer.
No full textCo-authorship network of authors selected papers, source: Formulated by author using VOS viewer.</p
Some Comments on the Question Whether Co-Occurrence Data Should Be Normalized
No full textIn a recent article in JASIST, L. Leydesdorff and L. Vaughan (2006) asserted that raw cocitation data should be analyzed directly, without first applying a normalization such as the Pearson correlation. In this communication, it is argued that there is nothing wrong with the widely adopted practice of normalizing cocitation data. One of the arguments put forward by Leydesdorff and Vaughan turns out to depend crucially on incorrect multidimensional scaling maps that are due to an error in the PROXSCAL program in SPSS.multidimensional scaling;PROXSCAL;Pearson correlation;author cocitation analysis;co-occurrence data;normalization
Co-authorship network of authors grouped by affiliated countries, source: Formulated by author using VOS viewer.
No full textCo-authorship network of authors grouped by affiliated countries, source: Formulated by author using VOS viewer.</p
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