130,756 research outputs found
MeSH term explosion and author rank improve expert recommendations
No full textInformation overload is an often-cited phenomenon that reduces the productivity, efficiency and efficacy of scientists. One challenge for scientists is to find appropriate collaborators in their research. The literature describes various solutions to the problem of expertise location, but most current approaches do not appear to be very suitable for expert recommendations in biomedical research. In this study, we present the development and initial evaluation of a vector space model-based algorithm to calculate researcher similarity using four inputs: 1) MeSH terms of publications; 2) MeSH terms and author rank; 3) exploded MeSH terms; and 4) exploded MeSH terms and author rank. We developed and evaluated the algorithm using a data set of 17,525 authors and their 22,542 papers. On average, our algorithms correctly predicted 2.5 of the top 5/10 coauthors of individual scientists. Exploded MeSH and author rank outperformed all other algorithms in accuracy, followed closely by MeSH and author rank. Our results show that the accuracy of MeSH term-based matching can be enhanced with other metadata such as author rank
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
"Closing the R&D Gap, Evaluating the Sources of R&D Spending"
No full textBoth spending and tax policies have been implemented in the United States with the goal of stimulating private sector research and development (R&D). Karier questions whether current R&D policy, especially the research and experimentation tax credit, can contribute to closing the gap between nondefense expenditures on R&D in the United States and such expenditures in other countries, such as Japan and Germany. He also explores possible changes to our current R&D policy to make it more effective.
Dispelling the Myths Behind First-author Citation Counts
No full textWe 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
Scholarly Communication and Publishing Lunch and Learn Talk #11: The ULS Open Access Author Fee Fund
No full textAt the May 2014 talk, you will learn about the ULS Open Access Author Fee Fund--what it is, why we do it, how it works, and how the program is going so far
The R&D Tax Incentives
No full textThis article sets out some background information and reflections of the author on the R&D tax incentive schemes included in the Common Corporate Tax Base (CCTB) Proposal. In particular the author analyzes the stimulus to private R&D through ad hoc tax incentives included in the CCTB Proposal and dives into the actual provisions included in the Proposal highlighting the most relevant issues connected with their design and interpretation. Moreover, the author explores the interaction between the CCTB Proposal and the granting by Member States of domestic R&D tax incentives
Measuring and Validating Emotional Intelligence as Performance or Self-Report
No full textThis is a study of emotional intelligence (EI). EI was measured by performance and self-report tasks. Data were also obtained on basic values, some standard personality dimensions such as those specified in the five-factor model, social adjustment and several scales of impression management. Criteria were loneliness, work-family life balance and Internet addiction, and also measures of emotional and value deviance. Participants were college students in a business education program who participated anonymously in the extensive test session, which took about six hours to complete. It was found that EI measures - both self-report and performance - intercorrelated as expected, and that EI was strongly related as expected to criteria. People high in EI reported less loneliness, less Internet addiction and better work/studies - leisure/family balance. Impression management was more strongly related to self-report data than to performance. Self-report data were to a large extent accounted for by measures of personality according to the five-factor model, but performance measures were not. Finally, the extent of faking was measured and controlled for.emotional intelligence; personality; five-factor model; and impression management
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