Maps of science as interdisciplinary discourse: co-citation contexts and the role of analogy

Small, Henry

doi:10.1007/s11192-009-0121-z

Cited by 46 publications

(32 citation statements)

References 25 publications

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“…Those categories have been used in several previous studies of interdisciplinary constellations in various scientific contexts, where also the methodological problems inherent in using the WoS categories for classification of interdisciplinary research have been thoroughly discussed (e.g. Gowanlock and Gazan 2013;Porter and Rafols 2009;Small 2010). In spite of these problems, for reasons of simplicity and convenience, the categories are used here to create the exemplary visualization shown in figure 11, where all articles published in 2012, and all older articles cited in that year, are included.…”

Section: Qualifying Impactmentioning

confidence: 99%

Qualifying the performance evaluation of Big Science beyond productivity, impact and costs

Heidler

Hallonsten

2015

Scientometrics

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The use of quantitative performance measures to evaluate the productivity, impact and quality of research has spread to almost all parts of public R&D systems, including Big Science where traditional measures of technical reliability of instruments and user oversubscription have been joined by publication counts to assess scientific productivity. But such performance assessment has been shown to lead to absurdities, as the calculated average cost of single journal publications easily may reach hundreds of millions of dollars. In this article, the issue of productivity and impact is therefore further qualified by the use of additional measures such as the immediacy index as well as network analysis to evaluate qualitative aspects of the impact of contemporary Big Science labs. Connecting to previous work within what has been called "facilitymetrics", the article continues the search for relevant bibliometric measures of the performance of Big Science labs with the use of a case study of a recently opened facility that is advertised as contributing to "breakthrough" research, by using several more measures and thus qualifying the topic of performance evaluation in contemporary Big Science beyond simple counts of publications, citations, and costs.

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Section: Qualifying Impactmentioning

confidence: 99%

Qualifying the performance evaluation of Big Science beyond productivity, impact and costs

Heidler

Hallonsten

2015

Scientometrics

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“…Van Leeuwen and Tijssen (2000) studied to what extent disciplines are interrelated by using journal-to-journal cross-disciplinary citation analysis. Small (2010) showed that the share of interdisciplinary (co-citation) links increases with level of aggregation, where a high level corresponds to a global map of links. Following this, the citation analysis in this study is expected to yield lower cross-field citation counts than, for example, a cross-field citation analysis of information science and computer science.…”

Section: Previous Researchmentioning

confidence: 99%

“…Journal-to-journal citations were not analyzed due to two main reasons. First, a problem with analyzing journal-to-journal citations is that journals can be interdisciplinary (Small, 2010), and second, there are differences in where research papers are published. In these sets, web mining has a heavy overweight in conference papers (68% of the retrieved papers), and webometrics is heavily dominated by articles (77%).…”

Section: Citation Analysismentioning

confidence: 99%

Webometrics benefitting from web mining? An investigation of methods and applications of two research fields

Lorentzen

2014

Scientometrics

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Webometrics and web mining are two fields where research is focused on quantitative analyses of the web. This literature review outlines definitions of the fields, and then focuses on their methods and applications. It also discusses the potential of closer contact and collaboration between them. A key difference between the fields is that webometrics has focused on exploratory studies, whereas web mining has been dominated by studies focusing on development of methods and algorithms. Differences in type of data can also be seen, with webometrics more focused on analyses of the structure of the web and web mining more focused on web content and usage, even though both fields have been embracing the possibilities of user generated content. It is concluded that research problems where big data is needed can benefit from collaboration between webometricians, with their tradition of exploratory studies, and web miners, with their tradition of developing methods and algorithms.

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“…Combined with citation and bibliometric analysis, which uses citation data, these methods provide an effective way to better examine the nature or characteristics of inter-disciplinary activity. Recent studies have utilized citation information and constructed a network analysis to quantitatively and visually measure inter-disciplinarity (Kaur et al, 2012;Schoolman et al, 2012;Small, 2009;Xie et al, 2015;Yang and Heo, 2014). Although this approach offers some value in individual measurement, it is difficult to apply in macro scale analysis, including the S&E field.…”

Section: Introductionmentioning

confidence: 99%

“…Although this approach offers some value in individual measurement, it is difficult to apply in macro scale analysis, including the S&E field. Furthermore, previous studies initially assumed the inter-disciplinarity of certain research and used such assumptions as basis for later analyses (Kaur et al, 2012;Schoolman et al, 2012;Small, 2009;Xie et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Quantitative Definitions of Collaborative Research Fields in Science and Engineering

Schwartz¹,

Park²,

Lee³

2016

KTIS

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Practical methodology for categorizing collaborative disciplines or research in a quantitative manner is presented by developing a Correlation Matrix of Major Disciplines (CMMD) using bibliometric data collected between 2009 and 2014. First, 21 major disciplines in science and engineering are defined based on journal publication frequency. Second, major disciplines using a comparing discipline correlation matrix is created and correlation score using CMMD is calculated based on an analyzer function that is given to the matrix elements. Third, a correlation between the major disciplines and 14 research fields using CMMD is calculated for validation. Collaborative researches are classified into three groups by partially accepting the definition of pluri-discipline from peer review manual, European Science Foundation, inner-discipline, inter-discipline and cross-discipline. Applying simple categorization criteria identifies three groups of collaborative research and also those results can be visualized. Overall, the proposed methodology supports the categorization for each research field. KeywordsCollaborative research, inner-disciplinary research, interdisciplinary research, cross-disciplinary research, quantification method, correlation matrix of major disciplines(CMMD), bibliometric data

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Maps of science as interdisciplinary discourse: co-citation contexts and the role of analogy

Cited by 46 publications

References 25 publications

Qualifying the performance evaluation of Big Science beyond productivity, impact and costs

Qualifying the performance evaluation of Big Science beyond productivity, impact and costs

Webometrics benefitting from web mining? An investigation of methods and applications of two research fields

Quantitative Definitions of Collaborative Research Fields in Science and Engineering

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