-
Falkingham, L.T.; Reeves, R.: Context analysis : a technique for analysing research in a field, applied to literature on the management of R&D at the section level (1998)
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- Abstract
- Context analysis is a new method for appraising a body of publications. the process consists of creating a database of attributes assigned to each paper by the reviewer and then looking for interesting relationships in the data. Assigning the attributes requires an understanding of the subject matter of the papers. Presents findings about one particular research field, Management of R&D at the Section Level. The findings support the view that this body of academic publications does not meet the needs of practitioner R&D managers. Discusses practical aspects of how to apply the method in other fields
- Date
- 22. 5.1999 19:18:46
-
Huang, M.-H.; Huang, W.-T.; Chang, C.-C.; Chen, D. Z.; Lin, C.-P.: The greater scattering phenomenon beyond Bradford's law in patent citation (2014)
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- Abstract
- Patent analysis has become important for management as it offers timely and valuable information to evaluate R&D performance and identify the prospects of patents. This study explores the scattering patterns of patent impact based on citations in 3 distinct technological areas, the liquid crystal, semiconductor, and drug technological areas, to identify the core patents in each area. The research follows the approach from Bradford's law, which equally divides total citations into 3 zones. While the result suggests that the scattering of patent citations corresponded with features of Bradford's law, the proportion of patents in the 3 zones did not match the proportion as proposed by the law. As a result, the study shows that the distributions of citations in all 3 areas were more concentrated than what Bradford's law proposed. The Groos (1967) droop was also presented by the scattering of patent citations, and the growth rate of cumulative citation decreased in the third zone.
- Date
- 22. 8.2014 17:11:29
-
Leydesdorff, L.; Bornmann, L.; Wagner, C.S.: ¬The relative influences of government funding and international collaboration on citation impact (2019)
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- Abstract
- A recent publication in Nature reports that public R&D funding is only weakly correlated with the citation impact of a nation's articles as measured by the field-weighted citation index (FWCI; defined by Scopus). On the basis of the supplementary data, we up-scaled the design using Web of Science data for the decade 2003-2013 and OECD funding data for the corresponding decade assuming a 2-year delay (2001-2011). Using negative binomial regression analysis, we found very small coefficients, but the effects of international collaboration are positive and statistically significant, whereas the effects of government funding are negative, an order of magnitude smaller, and statistically nonsignificant (in two of three analyses). In other words, international collaboration improves the impact of research articles, whereas more government funding tends to have a small adverse effect when comparing OECD countries.
- Date
- 8. 1.2019 18:22:45
-
Persson, O.; Melin, G.: Equalization, growth and integration of science (1996)
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- Abstract
- Presents a study of the production of scientific papers, coauthorships and R&D expenditures in the OECD countries. Discusses the distribution of papers in the journal 'Science' by OECD country in comparison with 'Science Citation Index' papers as a whole and compares these to the distribution of R&D investments
-
Liu, D.-R.; Shih, M.-J.: Hybrid-patent classification based on patent-network analysis (2011)
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- Date
- 22. 1.2011 13:04:21
-
Cerda-Cosme, R.; Méndez, E.: Analysis of shared research data in Spanish scientific papers about COVID-19 : a first approach (2023)
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- Abstract
- During the coronavirus pandemic, changes in the way science is done and shared occurred, which motivates meta-research to help understand science communication in crises and improve its effectiveness. The objective is to study how many Spanish scientific papers on COVID-19 published during 2020 share their research data. Qualitative and descriptive study applying nine attributes: (a) availability, (b) accessibility, (c) format, (d) licensing, (e) linkage, (f) funding, (g) editorial policy, (h) content, and (i) statistics. We analyzed 1,340 papers, 1,173 (87.5%) did not have research data. A total of 12.5% share their research data of which 2.1% share their data in repositories, 5% share their data through a simple request, 0.2% do not have permission to share their data, and 5.2% share their data as supplementary material. There is a small percentage that shares their research data; however, it demonstrates the researchers' poor knowledge on how to properly share their research data and their lack of knowledge on what is research data.
- Date
- 21. 3.2023 19:22:02
-
Bornmann, L.; Mutz, R.: From P100 to P100' : a new citation-rank approach (2014)
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- Date
- 22. 8.2014 17:05:18
-
Harries, G.; Wilkinson, D.; Price, L.; Fairclough, R.; Thelwall, M.: Hyperlinks as a data source for science mapping : making sense of it all (2005)
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-
Ahlgren, P.; Jarneving, B.; Rousseau, R.: Requirements for a cocitation similarity measure, with special reference to Pearson's correlation coefficient (2003)
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- Abstract
- Ahlgren, Jarneving, and. Rousseau review accepted procedures for author co-citation analysis first pointing out that since in the raw data matrix the row and column values are identical i,e, the co-citation count of two authors, there is no clear choice for diagonal values. They suggest the number of times an author has been co-cited with himself excluding self citation rather than the common treatment as zeros or as missing values. When the matrix is converted to a similarity matrix the normal procedure is to create a matrix of Pearson's r coefficients between data vectors. Ranking by r and by co-citation frequency and by intuition can easily yield three different orders. It would seem necessary that the adding of zeros to the matrix will not affect the value or the relative order of similarity measures but it is shown that this is not the case with Pearson's r. Using 913 bibliographic descriptions form the Web of Science of articles form JASIS and Scientometrics, authors names were extracted, edited and 12 information retrieval authors and 12 bibliometric authors each from the top 100 most cited were selected. Co-citation and r value (diagonal elements treated as missing) matrices were constructed, and then reconstructed in expanded form. Adding zeros can both change the r value and the ordering of the authors based upon that value. A chi-squared distance measure would not violate these requirements, nor would the cosine coefficient. It is also argued that co-citation data is ordinal data since there is no assurance of an absolute zero number of co-citations, and thus Pearson is not appropriate. The number of ties in co-citation data make the use of the Spearman rank order coefficient problematic.
- Date
- 9. 7.2006 10:22:35
-
Egghe, L.; Rousseau, R.: Averaging and globalising quotients of informetric and scientometric data (1996)
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- Source
- Journal of information science. 22(1996) no.3, S.165-170
-
Asonuma, A.; Fang, Y.; Rousseau, R.: Reflections on the age distribution of Japanese scientists (2006)
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- Date
- 22. 7.2006 15:26:24
-
Raan, A.F.J. van: Scaling rules in the science system : influence of field-specific citation characteristics on the impact of research groups (2008)
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- Date
- 22. 3.2009 19:03:12
- Footnote
- Vgl. auch: Costas, R., M. Bordons u. T.N. van Leeuwen u.a.: Scaling rules in the science system: Influence of field-specific citation characteristics on the impact of individual researchers. In: Journal of the American Society for Information Science and Technology. 60(2009) no.4, S.740-753.
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Ntuli, H.; Inglesi-Lotz, R.; Chang, T.; Pouris, A.: Does research output cause economic growth or vice versa? : evidence from 34 OECD countries (2015)
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- Date
- 8. 7.2015 22:00:42
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Hjerppe, R.: ¬An outline of bibliometrics and citation analysis (1980)
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- Type
- r
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Ravichandra Rao, I.K.; Sahoo, B.B.: Studies and research in informetrics at the Documentation Research and Training Centre (DRTC), ISI Bangalore (2006)
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- Abstract
- Contributions of DRTC to informetric studies and research are discussed. A report on recent work - a quantitative country-wise analysis of software literature based on the data from two bibliographic databases i.e. COMPENDEX and INSPEC is presented. The number of countries involved in R & D activities in software in the most productive group is increasing. The research contribution on software is decreasing in developed countries as compared to that in developing and less developed countries. India 's contribution is only 1.1% and it has remained constant over the period of 12 years 1989-2001. The number of countries involved in R&D activities in software has been increasing in the 1990s. It is also noted that higher the budget for higher education, higher the number of publications; and that higher the number of publications, higher the export as well as the domestic consumption of software.
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Yan, E.: Disciplinary knowledge production and diffusion in science (2016)
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- Abstract
- This study examines patterns of dynamic disciplinary knowledge production and diffusion. It uses a citation data set of Scopus-indexed journals and proceedings. The journal-level citation data set is aggregated into 27 subject areas and these subjects are selected as the unit of analysis. A 3-step approach is employed: the first step examines disciplines' citation characteristics through scientific trading dimensions; the second step analyzes citation flows between pairs of disciplines; and the third step uses egocentric citation networks to assess individual disciplines' citation flow diversity through Shannon entropy. The results show that measured by scientific impact, the subjects of Chemical Engineering, Energy, and Environmental Science have the fastest growth. Furthermore, most subjects are carrying out more diversified knowledge trading practices by importing higher volumes of knowledge from a greater number of subjects. The study also finds that the growth rates of disciplinary citations align with the growth rates of global research and development (R&D) expenditures, thus providing evidence to support the impact of R&D expenditures on knowledge production.
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Costas, R.; Bordons, M.; Leeuwen, T.N. van; Raan, A.F.J. van: Scaling rules in the science system : Influence of field-specific citation characteristics on the impact of individual researchers (2009)
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- Date
- 22. 3.2009 19:02:48
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Costas, R.; Zahedi, Z.; Wouters, P.: ¬The thematic orientation of publications mentioned on social media : large-scale disciplinary comparison of social media metrics with citations (2015)
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- Date
- 20. 1.2015 18:30:22
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Rotolo, D.; Leydesdorff, L.: Matching Medline/PubMed data with Web of Science: A routine in R language (2015)
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- Abstract
- We present a novel routine, namely medlineR, based on the R language, that allows the user to match data from Medline/PubMed with records indexed in the ISI Web of Science (WoS) database. The matching allows exploiting the rich and controlled vocabulary of medical subject headings (MeSH) of Medline/PubMed with additional fields of WoS. The integration provides data (e.g., citation data, list of cited reference, list of the addresses of authors' host organizations, WoS subject categories) to perform a variety of scientometric analyses. This brief communication describes medlineR, the method on which it relies, and the steps the user should follow to perform the matching across the two databases. To demonstrate the differences from Leydesdorff and Opthof (Journal of the American Society for Information Science and Technology, 64(5), 1076-1080), we conclude this artcle by testing the routine on the MeSH category "Burgada syndrome."
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Shelton, R.D.; Leydesdorff, L.: Publish or patent : bibliometric evidence for empirical trade-offs in national funding strategies (2012)
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- Abstract
- Multivariate linear regression models suggest a trade-off in allocations of national research and development (R&D). Government funding and spending in the higher education sector encourage publications as a long-term research benefit. Conversely, other components such as industrial funding and spending in the business sector encourage patenting. Our results help explain why the United States trails the European Union in publications: The focus in the United States is on industrial funding-some 70% of its total R&D investment. Likewise, our results also help explain why the European Union trails the United States in patenting, since its focus on government funding is less effective than industrial funding in predicting triadic patenting. Government funding contributes negatively to patenting in a multiple regression, and this relationship is significant in the case of triadic patenting. We provide new forecasts about the relationships of the United States, the European Union, and China for publishing; these results suggest much later dates for changes than previous forecasts because Chinese growth has been slowing down since 2003. Models for individual countries might be more successful than regression models whose parameters are averaged over a set of countries because nations can be expected to differ historically in terms of the institutional arrangements and funding schemes.
