Search (9 results, page 1 of 1)

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Abstract

This paper presents a test of the validity of using Google Scholar to evaluate the publications of researchers by comparing the premises on which its search engine, PageRank, is based, to those of Garfield's theory of citation indexing. It finds that the premises are identical and that PageRank and Garfield's theory of citation indexing validate each other.

Date

17.12.2013 11:02:22

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Abstract

Traditional citation analysis has been widely applied to detect patterns of scientific collaboration, map the landscapes of scholarly disciplines, assess the impact of research outputs, and observe knowledge transfer across domains. It is, however, limited, as it assumes all citations are of similar value and weights each equally. Content-based citation analysis (CCA) addresses a citation's value by interpreting each one based on its context at both the syntactic and semantic levels. This paper provides a comprehensive overview of CAA research in terms of its theoretical foundations, methodical approaches, and example applications. In addition, we highlight how increased computational capabilities and publicly available full-text resources have opened this area of research to vast possibilities, which enable deeper citation analysis, more accurate citation prediction, and increased knowledge discovery.

Date

22. 8.2014 16:52:04

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Abstract

Historically, co-citation models have been based only on bibliographic information. Full-text analysis offers the opportunity to significantly improve the quality of the signals upon which these co-citation models are based. In this work we study the effect of reference proximity on the accuracy of co-citation clusters. Using a corpus of 270,521 full text documents from 2007, we compare the results of traditional co-citation clustering using only the bibliographic information to results from co-citation clustering where proximity between reference pairs is factored into the pairwise relationships. We find that accounting for reference proximity from full text can increase the textual coherence (a measure of accuracy) of a co-citation cluster solution by up to 30% over the traditional approach based on bibliographic information.

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Abstract

This study proposes a new framework for citation content analysis (CCA), for syntactic and semantic analysis of citation content that can be used to better analyze the rich sociocultural context of research behavior. This framework could be considered the next generation of citation analysis. The authors briefly review the history and features of content analysis in traditional social sciences and its previous application in library and information science (LIS). Based on critical discussion of the theoretical necessity of a new method as well as the limits of citation analysis, the nature and purposes of CCA are discussed, and potential procedures to conduct CCA, including principles to identify the reference scope, a two-dimensional (citing and cited) and two-module (syntactic and semantic) codebook, are provided and described. Future work and implications are also suggested.

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Abstract

This article provides an overview of studies that have used citation analysis in the field of humanities in the period 1951 to 2010. The work is based on an exhaustive search in databases-particularly those in library and information science-and on citation chaining from papers on citation analysis. The results confirm that use of this technique in the humanities is limited, and although there was some growth in the 1970s and 1980s, it has stagnated in the past 2 decades. Most of the work has been done by research staff, but almost one third involves library staff, and 15% has been done by students. The study also showed that less than one fourth of the works used a citation database such as the Arts & Humanities Citation Index and that 21% of the works were in publications other than library and information science journals. The United States has the greatest output, and English is by far the most frequently used language, and 13.9% of the studies are in other languages.

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Abstract

Systematic reviews are essential for evaluating biomedical treatment options, but the growing size and complexity of the available biomedical literature combined with the rigor of the systematic review method mean that systematic reviews are extremely difficult and labor-intensive to perform. In this article, I propose a method of searching the literature by systematically mining the various types of citation relationships between articles. I then test the method by comparing its precision and recall to that of 14 published systematic reviews. The method successfully retrieved 74% of the studies included in these reviews and 90% of the studies it could reasonably be expected to retrieve. The method also retrieved fewer than half of the total number of publications retrieved by these reviews and can be performed in substantially less time. This suggests that the proposed method offers a promising complement to traditional text-based methods of literature identification and retrieval for systematic reviews.

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Abstract

In this study we investigate if articles suffering delayed recognition can at the same time be under-cited influential articles. Theoretically these two types of articles are independent, in the sense that suffering delayed recognition depends on the number and time distribution of received citations, while being an under-cited influential article depends only partially on the number of received (first generation) citations, and much more on second and third citation generations. Among 49 articles suffering delayed recognition we found 13 that are also under-cited influential. Based on a thorough investigation of these special cases we found that so-called authoritative citers play an important role in uniting the two different document types into a special citation chimera. Our investigation contributes to the classification of publications.

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Abstract

Previous analyses identified research on environmental tobacco smoke to be subject to strong fluctuations as measured by both quantitative and qualitative indicators. The evolution of search algorithms (based on the Web of Science and Web of Knowledge database platforms) was used to show the impact of errors of omission and commission in the outcomes of scientometric research. Optimization of the search algorithm led to the complete reassessment of previously published findings on the performance of environmental tobacco smoke research. Instead of strong continuous growth, the field of environmental tobacco smoke research was shown to experience stagnation or slow growth since mid-1990s when evaluated quantitatively. Qualitative analysis revealed steady but slow increase in the citation rate and decrease in uncitedness. Country analysis revealed the North-European countries as leaders in environmental tobacco smoke research (when the normalized results were evaluated both quantitatively and qualitatively), whereas the United States ranked first only when assessing the total number of papers produced. Scientometric research artifacts, including both errors of omission and commission, were shown to be capable of completely obscuring the real output of the chosen research field.

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Abstract

We present an analysis of data citation practices based on the Data Citation Index (DCI) (Thomson Reuters). This database launched in 2012 links data sets and data studies with citations received from the other citation indexes. The DCI harvests citations to research data from papers indexed in the Web of Science. It relies on the information provided by the data repository. The findings of this study show that data citation practices are far from common in most research fields. Some differences have been reported on the way researchers cite data: Although in the areas of science and engineering & technology data sets were the most cited, in the social sciences and arts & humanities data studies play a greater role. A total of 88.1% of the records have received no citation, but some repositories show very low uncitedness rates. Although data citation practices are rare in most fields, they have expanded in disciplines such as crystallography and genomics. We conclude by emphasizing the role that the DCI could play in encouraging the consistent, standardized citation of research data-a role that would enhance their value as a means of following the research process from data collection to publication.